 Subjects -> METEOROLOGY (Total: 106 journals)
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- Atmosphere, Vol. 14, Pages 906: Mobile Measurements of Atmospheric Methane
at Eight Large Landfills: An Assessment of Temporal and Spatial
Variability
Authors: Tian Xia, Sachraa G. Borjigin, Julia Raneses, Craig A. Stroud, Stuart A. Batterman
First page: 906
Abstract: Municipal solid waste landfills are major contributors to anthropogenic emissions of methane (CH4), which is the major component of natural gas, a potent greenhouse gas, and a precursor for the formation of tropospheric ozone. The development of sensitive, selective, and fast-response instrumentation allows the deployment of mobile measurement platforms for CH4 measurements at landfills. The objectives of this study are to use mobile monitoring to measure ambient levels of CH4 at eight large operating landfills in southeast Michigan, USA; to characterize diurnal, daily and spatial variation in CH4 levels; and to demonstrate the influence of meteorological factors. Elevated CH4 levels were typically found along the downwind side or corner of the landfill. Levels peaked in the morning, reaching 38 ppm, and dropped to near-baseline levels during midday. Repeat visits showed that concentrations were highly variable. Some variation was attributable to the landfill size, but both mechanistically-based dilution-type models and multivariate models identified that wind speed, boundary layer height, barometric pressure changes, and landfill temperature were key determinants of CH4 levels. Collectively, these four factors explained most (r2 = 0.89) of the variation in the maximum CH4 levels at the landfill visited most frequently. The study demonstrates the ability to assess spatial and temporal variation in CH4 levels at landfills using mobile monitoring along perimeter roads. Such monitoring can identify the location of leaks and the best locations for long-term emission monitoring using fixed site monitors.
Citation: Atmosphere
PubDate: 2023-05-23
DOI: 10.3390/atmos14060906
Issue No: Vol. 14, No. 6 (2023)
- Atmosphere, Vol. 14, Pages 907: Review of Jackson Herring’s Early
Work on Thermal Convection
Authors: Robert M. Kerr
First page: 907
Abstract: Jack Herring had three mid-1960s numerical papers on Rayleigh-Bénard thermal convection that might seem primitive by today’s standards, but already encapsulated many of the questions that are still being asked. All of them use severely truncated versions of the incompressible Navier–Stokes–Boussinesq equations with only one, or just a few, horizontal Fourier modes. In the first two papers, 1963 and 1964, the presented results used only one Fourier mode α and three variables. The single mode’s variables are its vertical velocity profile wα(z,t), its temperature profile θα(z,t) and the horizontally uniform vertical profile of the background temperature ψ(z,t). All of the second- and third-order terms are ignored except the convective heat flux wθ¯. The objective was to find asymptotic steady-state solutions. Each paper found evidence for the one-third Nusselt versus Rayleigh scaling of Nu∼Ra1/3, originally derived from Malkus’ maximum flux principle. The 1963 paper uses free-slip upper and lower boundaries, with magnitudes of Nu that are a factor of three larger than the experiments. In the 1964 paper, by introducing no-slip/rigid boundary conditions, the magnitude of Nu dropped to within 20% of the experimental values. Both Nu(Ra) relations are in good agreement with circa-1990 direct numerical simulations (DNS). This dependence upon the boundary condition at the walls suggests that to obtain physically realistic scaling, no-slip boundary conditions are necessary. The third paper is discussed only in terms of what it might have been aiming to accomplish and its relation to the earlier free-slip results.
Citation: Atmosphere
PubDate: 2023-05-23
DOI: 10.3390/atmos14060907
Issue No: Vol. 14, No. 6 (2023)
- Atmosphere, Vol. 14, Pages 908: Individual and Combined Effects of 3D
Buildings and Green Spaces on the Urban Thermal Environment: A Case Study
in Jinan, China
Authors: Jiayun Wang, Fei Meng, Huanhuan Lu, Yongqiang Lv, Tingting Jing
First page: 908
Abstract: This study aimed to accurately grasp the impact mechanism and change rule of buildings and green spaces on land surface temperature (LST), which is of great significance for alleviating urban heat islands (UHIs) and formulating adaptation measures. Taking Jinan, China, as the study area, combined multisource remote sensing data were used in this study to construct an index system of the influencing factors. We used a spatial regression model to explore the relative contribution of the influencing indicators on LST. We also drew a marginal utility curve to quantify the heating/cooling effect of the leading indicators. The results showed that, firstly, among the 3D building indicators, the leading indicators affecting LST were the degree of spatial convergence (SCD) and the building surface area (BSA). Among the green space indicators, the largest patch index (LPI), green coverage rate (GCR), and edge density (ED) were significantly negatively correlated with LST. Secondly, when we considered the 15 indicators comprehensively, SCD was the most influential indicator, with a contribution of 24.7%, and the contribution of the green space indicators to LST was significantly reduced. Thirdly, among the leading indicators, SCD was positively correlated with LST. When SCD was less than 60%, LST increased by about 0.38 °C for every 10% increase. When GCR > 44%, LST was significantly reduced, and when GCR > 62%, a cooling effect of 1.1 °C was observed. Beyond this threshold, the cooling effect will not improve significantly. This study shows that when 3D buildings are densely distributed and crowded, the cooling effect of green space will be limited to some extent by 3D buildings. The key to mitigating UHIs is to rationally configure and optimize the spatial structure of 3D buildings.
Citation: Atmosphere
PubDate: 2023-05-23
DOI: 10.3390/atmos14060908
Issue No: Vol. 14, No. 6 (2023)
- Atmosphere, Vol. 14, Pages 909: An MCDM Approach to Analytically Identify
the Air Pollutants’ Impact on Health
Authors: Rashmi Bhardwaj, Shanky Garg
First page: 909
Abstract: Air pollution is one of the deadliest and most important concerns of our era, and it not only impacts our environment but also our health. The consequences of poor air quality are not limited to just our lungs or our heart but also our brain and resulting in increased mortality rate of many countries every year. There are many effluents/pollutants present in the air that are harmful and cause diseases in humans which eventually lead to an increase in morbidity and mortality. Therefore, there is a need to identify those factors and evaluate the effect of pollution caused by air on the health of humans which is a prerequisite for the implementation of policies in preventing pollution. In this study, we model and evaluate the harmful impact of pollution caused by air on the health of humans by using a multi-criteria decision-making approach (MCDM). We have proposed a novel coupled model of the double modified (criteria importance through intercriteria correlation) CRITIC—technique for order of preference by similarity to ideal solution (TOPSIS) method (DMCTM) to identify and evaluate the factors of air pollution and its effect on health which overcome the disadvantage of bias while collecting the subjective data in the traditional TOPSIS method. To get a clear view of the framework proposed, a case study is conducted based on the methodology proposed in which we find that Xinxiang is the most polluted city in China among the five studied cities with SO2 as the major contributor, and the city experienced more pollution levels in 2022 and least in 2016, whereas there is a slight fluctuation in life expectancy with air pollution in the years 2015 and 2023.
Citation: Atmosphere
PubDate: 2023-05-23
DOI: 10.3390/atmos14060909
Issue No: Vol. 14, No. 6 (2023)
- Atmosphere, Vol. 14, Pages 910: Three-Dimensional Visualization of
Long-Range Atmospheric Transport of Crop Pathogens and Insect Pests
Authors: Marcel Meyer, William Thurston, Jacob W. Smith, Alan Schumacher, Sarah C. Millington, David P. Hodson, Keith Cressman, Christopher A. Gilligan
First page: 910
Abstract: Some of the most devastating crop diseases and insect pests can be transmitted by wind over extremely long distances. These low-probability but high-impact events can have severe consequences for crop production and food security by causing epidemic outbreaks or devastating insect infestations in previously uninfected geographic areas. Two prominent examples that have recently caused substantial damage to agricultural production are novel strains of wheat rusts and desert locust swarm infestations. Whilst quantitative estimates of long-range atmospheric transport events can be obtained using meteorological transport simulations, the exact characteristics of three-dimensional spatiotemporal dynamics of crop pathogen transport and insect flight on extremely large spatial scales, over entire regions and continents, remain largely unknown. Here, we investigate the feasibility and usefulness of new advanced geospatial data visualization methods for studying extremely long-distance airborne transmission of crop pathogens and insect pests. We combine field surveillance data and a Lagrangian Particle Dispersion Model with novel techniques from computer graphics to obtain, for the first time, detailed three-dimensional visual insights into airborne crop pathogen and insect pest transport on regional and continental scales. Visual insights into long-distance dispersal of pests and pathogens are presented as a series of short 3D movies. We use interactive three-dimensional visual data analysis for explorative examination of long-range atmospheric transport events from a selection of outbreak and infestation sites in East Africa and South East Asia. The practical usefulness of advanced 3D visualization methods for improving risk estimates and early warning is discussed in the context of two operational crop disease and insect pest management systems (for wheat rusts and desert locusts). The tools and methods introduced here can be applied to other pathogens, pests, and geographical areas and can improve understanding of risks posed to agricultural production by crop disease and insect pest transmission caused by meteorological extreme events.
Citation: Atmosphere
PubDate: 2023-05-23
DOI: 10.3390/atmos14060910
Issue No: Vol. 14, No. 6 (2023)
- Atmosphere, Vol. 14, Pages 911: Wave and Meso-Scale Eddy Climate in the
Arctic Ocean
Authors: Guojing Xing, Wei Shen, Meng Wei, Huan Li, Weizeng Shao
First page: 911
Abstract: Under global climate change, the characteristics of oceanic dynamics are gradually beginning to change due to melting sea ice. This study focused on inter-annual variation in waves and mesoscale eddies (radius > 40 km) in the Arctic Ocean from 1993 to 2021. The waves were simulated by a numerical wave model, WAVEWATCH-III (WW3), which included a parameterization of ice–wave interaction. The long-term wind data were from the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis (ERA-5), and current and sea level data from the HYbrid Coordinate Ocean Model (HYCOM)were used as the forcing fields. The simulated significant wave heights (SWHs) were validated against the 2012 measurements from the Jason-2 altimeter, yielding a 0.55 m root mean square error (RMSE) with a 0.95 correlation (COR). The seasonal variation in WW3-simulated SWH from 2021 to 2022 showed that the SWH was the lowest in summer (July and August 2021) and highest in winter (November 2021 to April 2022). This result indicates that parts of the Arctic could become navigable in summer. The mesoscale eddies were identified using a daily-averaged sea level anomalies (SLA) product with a spatial resolution of a 0.25° grid for 1993−2021. We found that the activity intensity (EKE) and radius of mesoscale eddies in the spatial distribution behaved in opposing ways. The analysis of seasonal variation showed that the increase in eddy activity could lead to wave growth. The amplitude of SWH peaks was reduced when the Arctic Oscillation Index (AOI) was <−1.0 and increased when the AOI was >0.5, especially in the case of swells. The amplitude of SWH oscillation was low, and the EKE and radius of eddies were relatively small. Although the radius and EKE of eddies were almost similar to the AOI, the waves also influenced the eddies.
Citation: Atmosphere
PubDate: 2023-05-23
DOI: 10.3390/atmos14060911
Issue No: Vol. 14, No. 6 (2023)
- Atmosphere, Vol. 14, Pages 912: Relevance and Reliability of Outdoor SO2
Monitoring in Low-Income Countries Using Low-Cost Sensors
Authors: Rosa Amalia González Rivero, Olivier Schalm, Arianna Alvarez Cruz, Erik Hernández Rodríguez, Mayra C. Morales Pérez, Daniellys Alejo Sánchez, Alain Martinez Laguardia, Werner Jacobs, Luis Hernández Santana
First page: 912
Abstract: In the Western world, the SO2 concentration in ambient air dropped to low levels, but some emission sources (e.g., merchant ships) and some regions (e.g., low-income countries) still emit substantial amounts of SO2. At those locations, SO2 monitoring is critical. However, low-income countries do not have much access to expensive reference instruments. Low-cost gas sensors might be an alternative, but it is unclear how reliable such measurements are. To evaluate the performance of the low-cost alternative, the same SO2 gas sensor has been subjected to three different calibration methods: (1) low-cost calibration performed in the tropical climate of Cuba; (2) high-end calibration performed in Belgium; (3) a field calibration at an air quality measuring station in Belgium. The first two methods showed similar trends, suggesting that the gas sensor can be calibrated with a low-cost method. The field calibration was hampered by the low SO2 concentrations. For the monitoring campaign in Cienfuegos, Cuba, the low-cost SO2 sensor calibrated by the low-cost method appeared to be sufficiently reliable. The reliability of the sensor increases with the increase in SO2 concentration, so it can be used in Cuba instead of Belgium.
Citation: Atmosphere
PubDate: 2023-05-23
DOI: 10.3390/atmos14060912
Issue No: Vol. 14, No. 6 (2023)
- Atmosphere, Vol. 14, Pages 913: Evaluation of ERA5-Simulated Temperature
and Its Extremes for Australia
Authors: Dipayan Choudhury, Fei Ji, Nidhi Nishant, Giovanni Di Virgilio
First page: 913
Abstract: Atmospheric reanalysis products offer high-resolution and long-term gridded datasets that can often be used as an alternative or a supplement to observational data. Although more accessible than typical observational data and deemed fit for climate change studies, reanalysis data can show biases resulting from data assimilation approaches. Thus, a thorough evaluation of the reanalysis product over the region and metric of study is critical. Here, we evaluate the performance of the latest generation of ECMWF reanalysis, ERA5, in simulating mean and extreme temperatures over Australia for 1979–2020 versus high-quality gridded observations. We find ERA5 generally simulates maximum and minimum temperatures reasonably well (mean bias ~1.5 °C), even though it underestimates/overestimates the daily maximum/minimum temperatures, leading to a cold bias for Tmax and a warm bias for Tmin. ERA5 also underestimates the decadal warming trend in both Tmax and Tmin compared to the observations. Furthermore, ERA5 struggles to simulate the temporal variability of Tmin, leading to a markedly worse skill in Tmin than Tmax. In terms of extreme indices, ERA5 is skilled at capturing the spatial and temporal patterns and trends of extremes, albeit with the presence of biases in each index. This can partially be attributed to the warm bias in the minimum temperature. Overall, ERA5 captures the mean and extreme temperature indices over the Australian continent reasonably well, warranting its potential to supplement observations in aiding climate change-related studies, downscaling for boundary conditions, and climate model evaluation.
Citation: Atmosphere
PubDate: 2023-05-24
DOI: 10.3390/atmos14060913
Issue No: Vol. 14, No. 6 (2023)
- Atmosphere, Vol. 14, Pages 914: Optimizing the Surrounding Building
Configuration to Improve the Cooling Ability of Urban Parks on Surrounding
Neighborhoods
Authors: Qian Han, Xinge Nan, Han Wang, Yanjun Hu, Zhiyi Bao, Hai Yan
First page: 914
Abstract: Urban parks reduce air temperatures within parks and surroundings by exerting the cooling island effect, significant for mitigating the urban microclimate. However, the park cooling effect may be influenced by the surrounding building configuration, and this needs to be studied in more detail, in particular, to explore how to maximize the cooling effect of parks by adjusting the surrounding building configuration. Thus, in this study, the effects of building height, building interval, and building orientation on the cooling effect of a small urban park were investigated using field measurements and ENVI-met numerical simulations. The results demonstrated that (1) building height, building interval, and building orientation all impact the park cooling effect, but their impacts vary. (2) Building height had the strongest effect on the park cooling intensity, and adjusting building height provided the maximum park cooling intensity (1.2 °C). (3) Building orientation had the most effect on the park cooling distance, 100 m downwind of the park. (4) The park cooling effect is best when the surrounding buildings were parallel to the prevailing wind direction, and the park cool island has the greatest intensity and range. This study can guide decision-makers in optimizing building configuration to maximize the park cooling effect.
Citation: Atmosphere
PubDate: 2023-05-24
DOI: 10.3390/atmos14060914
Issue No: Vol. 14, No. 6 (2023)
- Atmosphere, Vol. 14, Pages 915: Design, Modelling, and Experimental
Validation of a Glass U-Tube Mass Sensing Cantilever for Particulate
Direct-on-Line Emissions Measurement
Authors: Daniel Nicklin, Hamidreza Gohari Darabkhani
First page: 915
Abstract: The requirement to monitor and control industrial processes has increased over recent years, therefore innovative techniques are required to meet the demand for alternative methods of particulate measurement. Resonant mass sensors are now strong candidates for accurate mass measurement and are frequently used in many diverse fields of science and engineering. This paper presents the design, modelling, and optimal geometry selection for sensitivity improvement of a U-shaped glass tube as a resonant mass sensing cantilever with a view to becoming a component of particulate measurement equipment. Finite Element Analysis (FEA) was used to develop the system which was validated experimentally using a physical model. This paper focuses on both the proof of concept and the geometry selection of the sensor using analysis of the system sensitivity for best selection. Modal and harmonic analysis were undertaken across a range of commercially available glass tube sizes from 6 mm to 10 mm diameter, to determine the optimal geometry selection, validated with practical experimental data. Results show a consistent difference of 3–5% between the simulation and experimental results, showing strong correlation. This research provides a methodology on the development of using a U-shaped glass tube for accurate mass measurement with a view to exploring the design as a component of particulate emissions equipment. The experimental and simulation results confirm that the highest sensitivity is achieved when the geometry dimensions, and therefore the vacant mass of the tube, is reduced. The 6 mm diameter tube with the smallest bend radius was the most suitable design to meet the design criteria. The calibration curve was plotted to allow an unknown mass to be calculated, which gave an R2 value of 0.9984. All experimental work was repeated three times with results giving an average of 0.44% between the minimum and maximum showing strong linearity and suggesting the potential for implementation of the methodology in its intended application. The design provides possible solutions to some of the issues currently seen with particulate measurement from stationary sources.
Citation: Atmosphere
PubDate: 2023-05-24
DOI: 10.3390/atmos14060915
Issue No: Vol. 14, No. 6 (2023)
- Atmosphere, Vol. 14, Pages 916: Airborne Air Pollutant Emission
Characteristics of Mobile Vehicles in Taiwan
Authors: Jiun-Horng Tsai, Jian-You Chen, Hung-Lung Chiang
First page: 916
Abstract: This study examines the air pollutant emission characteristics, activity intensity, and trends of mobile sources from 2013 to 2021. The target pollutants include criteria pollutants (fine particulate matters, nitrogen oxides, and hydrocarbons) and hazardous air pollutants (benzene, formaldehyde, and BaP). The results indicated that the activity intensity levels of road mobile sources in Taiwan were148 × 109, 156 × 109, 159 × 109, and 155 × 109 km/year in 2013, 2016, 2019, and 2021, respectively, with the largest proportion attributed to gasoline passenger cars (42.6%), followed by four-stroke motorcycles (32.6%). An emission factor of PM2.5 was estimated by EPA’s MOVES (Motor Vehicle Emission Simulator) model, and the results showed that the emission sequence was diesel > gasoline > motorcycle; the NOx emission factor was estimated using the MOBILE6.2 model, and the results showed that the order was diesel > gasoline > motorcycle; the HC emission factor was compiled with the use of gasoline vehicle dynamometer data, and the results showed that motorcycle > gasoline vehicles. Further results showed that the emission sequence for benzene was motorcycle > gasoline ≥ diesel; the formaldehyde emission sequence was diesel > motorcycle ≥ gasoline. The BaP emission factors of different vehicle types were estimated using MOVES, and the emission factors of old heavy-duty diesel vehicles were the highest.
Citation: Atmosphere
PubDate: 2023-05-24
DOI: 10.3390/atmos14060916
Issue No: Vol. 14, No. 6 (2023)
- Atmosphere, Vol. 14, Pages 917: Dynamics and Determinants of
Farmers’ Perceptions about Causes and Impacts of Climate Change on
Agriculture in Saudi Arabia: Implications for Adaptation, Mitigation, and
Sustainability
Authors: Bader Alhafi Alotaibi, Azhar Abbas, Raza Ullah, Muhammad Imran Azeem, Abdus Samie, Muhammad Muddassir, Abduaziz Thabet Dabiah, Moodhi Raid, Tahira Sadaf
First page: 917
Abstract: Concerns over the potential harmful impacts of changing climate are strongly echoing around the globe. With its wide range of hazards to human societies, climate change is posing serious threats to human survival and impacting every aspect of human life, including food production systems. It is, therefore, imperative to gauge the local knowledge, perceptions, and adaptation capacity for the effective mitigation of the ill impacts of climate change. In this backdrop, the present study has been designed to investigate the perceptions of farmers regarding causes and impacts of climate change on agriculture. Required data were collected from the Madinah region in Saudi Arabia and analyzed to answer the following study questions: How do farmers perceive impacts of climate change' What factors affect their perceived impacts of climate change' Additionally, what factors affect their perception about the causes of climate change' Individual logit models were used to assess the impacts of various factors on perceived causes and perceived impacts of climate change on agriculture. A multinomial logit model was also employed to figure out significant determinants of perceived causes of climate change on agriculture. Results indicated that the most dominant perceived impacts of climate change are its effects on crop production, followed by drying water sources. The results also revealed that the age of the farmers had a positive effect on their perception of natural processes being the cause of climate change. Similarly, farming experience had an inverse effect on their perceptions regarding causes of climate change. The majority of the farmers seemed clear about the possible drivers of climate change in the country. In particular, about 79 percent of the farmers believed that GHGs and pollution are causing climate change in the country. The findings provide useful insights into farmers’ perceptions about causes and impacts of climate change and may be used by policymakers to strategically design extension and agricultural development initiatives for helping the farmers to implement sustainable agricultural practices to adapt to and lower the adverse impacts of climate change in the Kingdom.
Citation: Atmosphere
PubDate: 2023-05-24
DOI: 10.3390/atmos14060917
Issue No: Vol. 14, No. 6 (2023)
- Atmosphere, Vol. 14, Pages 918: Small-Scale Anisotropy in Stably
Stratified Turbulence; Inferences Based on Katabatic Flows
Authors: Eliezer Kit, Harindra J. S. Fernando
First page: 918
Abstract: The focus of the current study is on the anisotropy of stably stratified turbulence that is not only limited to large scales and an inertial subrange but also penetrates to small-scale turbulence in the viscous/dissipation subrange on the order of the Kolmogorov scale. The anisotropy of buoyancy forces is well-known, including ensuing effects such as horizontal layering and pancakes structures. Laboratory experiments in the nineties by Van Atta and his students showed that the anisotropy penetrates to very small scales, but their experiments were performed only at a relatively low Reλ (i.e., at Taylor Reynolds numbers) and, therefore, did not provide convincing evidence of anisotropy penetration into viscous sublayers. Nocturnal katabatic flows having configurations of stratified parallel shear flows and developing on mountain slopes provide high Reynolds number data for testing the notion of anisotropy at viscous scales, but obtaining appropriate time series of the data representing stratified shear flows devoid of unwarranted atmospheric factors is a challenge. This study employed the “in situ” calibration of multiple hot-film-sensors collocated with a sonic anemometer that enabled obtaining a 90 min continuous time series of a “clean” katabatic flow. A detailed analysis of the structure functions was conducted in the inertial and viscous subranges at an Reλ around 1250. The results of DNS simulations by Kimura and Herring were employed for the interpretation of data.
Citation: Atmosphere
PubDate: 2023-05-24
DOI: 10.3390/atmos14060918
Issue No: Vol. 14, No. 6 (2023)
- Atmosphere, Vol. 14, Pages 919: On the Mechanisms of a Snowstorm
Associated with a Low-Level Cold Front and Low-Level Jet in the Western
Mountainous Region of the Junggar Basin, Xinjiang, Northwest China
Authors: He, Abulikemu, Mamtimin, Li, Abulimiti, An, Aireti, Zhou, Sun, Li, Yuan, Xi
First page: 919
Abstract: Snowstorms frequently hit large parts of the Northern Hemisphere, and their causative factors have been drawing increasing attention in recent years. As the first in-depth study on the mechanisms of a snowstorm associated with a low-level cold front (LLCF) and low-level westerly jet (LLWJ) in the western mountainous region of the Junggar Basin, Xinjiang, based on both observations and numerical simulation, the major findings of this work are as follows: At the early stage, instabilities were mainly dominated by inertial instability (II) occurring near the core region of the LLWJ, while the lower level was mainly controlled by the baroclinic component of moist potential vorticity (MPV2), which was mainly contributed by the vertical shear of the horizontal wind, which is also located near the LLWJ. At the later stage, II was released significantly, whereas the MPV2 still supported snowfall clouds. Further analysis based on the decomposition of the frontogenetical forcing required for the release of the instabilities indicated that the slantwise term was the major contributor, whereas convergence and deformation also played significant roles at low levels above the windward slope. The slantwise term resulted from the combined effects of baroclinicity due to the LLCF and the inhomogeneity of the momentum due to the LLWJ.
Citation: Atmosphere
PubDate: 2023-05-24
DOI: 10.3390/atmos14060919
Issue No: Vol. 14, No. 6 (2023)
- Atmosphere, Vol. 14, Pages 920: Turbulence along the Runway Glide Path:
The Invisible Hazard Assessment Based on a Wind Tunnel Study and
Interpretable TPE-Optimized KTBoost Approach
Authors: Afaq Khattak, Jianping Zhang, Pak-Wai Chan, Feng Chen
First page: 920
Abstract: Aircraft landings can be dangerous near airport runways due to wind variability. As a result, an aircraft could potentially miss an approach or divert off its flight path. In this study, turbulence intensity along the runway glide path was investigated using a scaled-down model of Hong Kong International Airport (HKIA) and the complex terrain nearby built in a TJ-3 atmospheric boundary layer wind tunnel. Different factors, including the effect of terrain, distance from the runway threshold, assigned approach runway, wind direction, and wind speed, were taken into consideration. Next, based on the experimental results, we trained and tested a novel tree-structured Parzen estimator (TPE)-optimized kernel and tree-boosting (KTBoost) model. The results obtained by the TPE-optimized KTBoost model outperformed other advanced machine learning models in terms of MAE (0.83), MSE (1.44), RMSE (1.20), and R2 (0.89). The permutation-based importance analysis using the TPE-optimized KTBoost model also revealed that the top three factors that contributed to the high turbulence intensity were the effect of terrain, distance from the runway threshold, and wind direction. The presence of terrain, the shorter distance from the runway, and the wind direction from 90 degrees to 165 degrees all contributed to high turbulence intensity.
Citation: Atmosphere
PubDate: 2023-05-24
DOI: 10.3390/atmos14060920
Issue No: Vol. 14, No. 6 (2023)
- Atmosphere, Vol. 14, Pages 921: Landscape as a Palimpsest for Energy
Transition: Correlations between the Spatial Development of
Energy-Production Infrastructure and Climate-Mitigation Goals
Authors: Lobosco, Tinti, Magagnoli, Mencarini, Mannucci, Ferrero
First page: 921
Abstract: The spatial footprint of energy infrastructures requires a re-evaluation of design and planning processes, especially in relation to the sustainable development goals enshrined in the United Nations 2030 Agenda. This study investigates the Ravenna area (Italy)’s transition potential towards renewable energy sources, considering their spatial interaction with the landscape and the environment. The primary objective is to identify the opportunities and limitations associated with each type of renewable energy production and provide indications for the strategic actions needed to achieve total emissions reduction by 2050. The methodology applied involves several steps to compare both the efficiency and the spatial arrangements of alternative mono-energy scenarios over time. In order to manage the uncertainty inherent in technological development and the variability of territorial policies, the study puts forward the hypothesis of a mixed strategy capable of structuring the energy transition on the specificities of the local landscape palimpsest by identifying location criteria and related impacts. The research demonstrates how site-specific assessments are important to inform resilient strategic choices, and provide decision-makers and stakeholders with data and spatialized representations of future scenarios to discuss and share.
Citation: Atmosphere
PubDate: 2023-05-24
DOI: 10.3390/atmos14060921
Issue No: Vol. 14, No. 6 (2023)
- Atmosphere, Vol. 14, Pages 922: Analysis of Precipitation Process and
Operational Precipitation Enhancement in Panxi Region Based on Cloud
Parameters Retrievals from China’s Next−Generation
Geostationary Meteorological Satellite FY−4A
Authors: Xiaomei Guo, Dan Lin, Fan Wu
First page: 922
Abstract: Geostationary meteorological satellite data with high spatial and temporal resolution can be used to retrieve cloud physical parameters, which has significant advantages in tracking cloud evolution and development. Based on satellite multispectral RGB composite image and cloud physical analysis methods, we quantitatively analyze the evolution characteristics of cloud parameters in the pre-, mid- and post-artificially influenced weather process, explore the application potential benefits of satellite data in monitoring the operating conditions of the artificially influenced weather in the Panxi region, and verify the feasibility analysis of the evaluation of their effects. In this study, cloud parameters such as cloud particle effective radius (Re), cloud liquid water path (LWP), cloud ice water path (IWP), and cloud top height and temperature (CTH and CTT) are retrieved using FY−4A satellite data. For the Panxi region, the evolution characteristics of typical cloud parameters in the affected area before and after two aircraft artificial operational precipitation enhancements are analyzed. The results show that the satellite retrieval of cloud characteristic parameters in the Panxi region has good application value, which can be used to guide the artificial Operational Precipitation Enhancement. In this precipitation process, there are solid particles in the upper layer cloud and supercooled water in the lower layer cloud. After the cold cloud catalysis, the cloud top height, liquid water and ice water content, particle effective radius and ground precipitation in the operational area increased, and the cloud top temperature decreased. Thus, it effectively alleviated the drought in the Panxi region. The satellite retrieval of cloud characteristic parameters in the Panxi region has a good application value, which can provide a basis and guidance for future weather modification operations in the Panxi region.
Citation: Atmosphere
PubDate: 2023-05-25
DOI: 10.3390/atmos14060922
Issue No: Vol. 14, No. 6 (2023)
- Atmosphere, Vol. 14, Pages 923: Impacts of Climate and Anthropogenic
Disturbances on Vegetation Structure and Functions
Authors: Wentao Zhang, Shuyao Wu
First page: 923
Abstract: Vegetation serves as a habitat for various wildlife species, provides crucial ecosystem services to society, and plays a critical role in regulating the global climate [...]
Citation: Atmosphere
PubDate: 2023-05-25
DOI: 10.3390/atmos14060923
Issue No: Vol. 14, No. 6 (2023)
- Atmosphere, Vol. 14, Pages 924: Development and Field Testing of an Online
Monitoring System for Atmospheric Particle-Bound Reactive Oxygen Species
(ROS)
Authors: Yuan Liu, Xiancheng Tang, Zhiwei Zhang, Ling Li, Jianmin Chen
First page: 924
Abstract: Excessive accumulation of reactive oxygen species (ROS) in the body can lead to a redox imbalance and result in cellular and tissue damage. Since ROS are highly reactive, traditional offline methods may underestimate their true concentration. In this study, we developed an online monitoring system for particle-bound ROS based on the fluorescent probe 2′,7′-dichlorofluorescin (DCFH), which consists of an Aerosol Collector and a Fluorescence Detector. The performance of the system was evaluated in terms of collection efficiency, instrument calibration, and comparison with offline methods. The results demonstrate that the collection efficiency of the system is over 93%, the calibration correlation coefficient (R2) is 99.75%, and the online system reduces ROS loss due to offline methods by more than 60%. The system has a temporal resolution of 20 min and the limit of detection of the system was 1.9 nmol H2O2/m3. Field observations revealed that particle-bound ROS exhibited similar diurnal variations to O3, and photochemical reactions were the main factors affecting its diurnal variation.
Citation: Atmosphere
PubDate: 2023-05-25
DOI: 10.3390/atmos14060924
Issue No: Vol. 14, No. 6 (2023)
- Atmosphere, Vol. 14, Pages 925: Spatiotemporal Changes in Water Yield
Function and Its Influencing Factors in the Tibetan Plateau in the Past 20
Years
Authors: Lingfeng Lv, Longbin Han, Xin Wen, Huaiyong Shao, Shuhan Liu
First page: 925
Abstract: The Tibetan Plateau, known as the “Water Tower of Asia”, has made important contributions to global climate regulation and water conservation. With global climate change and water shortages, the yield and reserves of water on the Tibetan Plateau have undergone obvious changes, and its water yield function and water conservation function have gradually attracted widespread attention. The results show that the total water yield in the past 20 years is 128,403.06 billion m3, spatially reduced from southeast to northwest, and the interannual variation is large but increases slowly overall. The water yield capacity is higher in the areas of less than 3000 m and 3500~4500 m, and it is stronger with the increase in slope. The water yield capacity is extremely strong in the middle and north subtropical zone. Ecological zones with high water yield capacity are mostly covered with woodland and alpine meadows. The precipitation (P) is the dominant factor in the water yield function before actual evapotranspiration (AET) = 500 mm, and then the negative force of AET is enhanced. High altitude inhibits the positive effect of the normalized vegetation index (NDVI), and the water yield at altitudes of less than 3000 m shows an almost linear relationship with the leaf area index (LAI). When LAI > 0.2, the slower the slope, the higher the water yield and the lower the growth rate. The spatial distribution of P change and water yield change is consistent and significantly positively correlated; P and NDVI changes positively affected changes in water yield, while AET and LAI changes had the opposite effect. In summary, combined with topographic factors, this study emphasizes the influence of climate and vegetation changes on the spatiotemporal changes in water yield on the Tibetan Plateau, which can provide a theoretical basis for the assessment and prediction of water yield capacity and water conservation capacity in this area.
Citation: Atmosphere
PubDate: 2023-05-25
DOI: 10.3390/atmos14060925
Issue No: Vol. 14, No. 6 (2023)
- Atmosphere, Vol. 14, Pages 926: Application of Functional Principal
Component Analysis in the Spatiotemporal Land-Use Regression Modeling of
PM2.5
Authors: Mahmood Taghavi, Ghader Ghanizadeh, Mohammad Ghasemi, Alessandro Fassò, Gerard Hoek, Kiavash Hushmandi, Mehdi Raei
First page: 926
Abstract: Functional data are generally curves indexed over a time domain, and land-use regression (LUR) is a promising spatial technique for generating high-resolution spatial estimation of retrospective long-term air pollutants. We developed a methodology for the novel functional land-use regression (FLUR) model, which provides high-resolution spatial and temporal estimations of retrospective pollutants. Long-term fine particulate matter (PM2.5) in the megacity of Tehran, Iran, was used as the practical example. The hourly measured PM2.5 concentrations were averaged for each hour and in each air monitoring station. Penalized smoothing was employed to construct the smooth PM2.5 diurnal curve using averaged hourly data in each of the 30 stations. Functional principal component analysis (FPCA) was used to extract FPCA scores from pollutant curves, and LUR models were fitted on FPCA scores. The mean of all PM2.5 diurnal curves had a maximum of 39.58 µg/m3 at 00:26 a.m. and a minimum of 29.27 µg/m3 at 3:57 p.m. The FPCA explained about 99.5% of variations in the observed diurnal curves across the city using just three components. The evaluation of spatially predicted long-term PM2.5 diurnal curves every 15 min provided a series of 96 high-resolution exposure maps. The presented methodology and results could benefit future environmental epidemiological studies.
Citation: Atmosphere
PubDate: 2023-05-25
DOI: 10.3390/atmos14060926
Issue No: Vol. 14, No. 6 (2023)
- Atmosphere, Vol. 14, Pages 927: Response of Runoff Change to Extreme
Authors: Luhua Wu, Dan Chen, Dongni Yang, Guangjie Luo, Jinfeng Wang, Fei Chen
First page: 927
Abstract: Identifying the response of runoff changes to extreme climate evolution was of great scientific significance for the rational regulation of watershed water resources and the prevention of hydrological disasters. However, the time–frequency response relationships were not clear. The Yinjiang River watershed, a typical watershed with karst trough valley areas, was chosen to identify the impact of different climatic driving factors on runoff changes from 1984 to 2015. Continuous wavelet transform (CWT), cross-wavelet transform (XWT), and wavelet coherence transform (WTC) were performed to study the response relationship and time–frequency effect between runoff changes and extreme climate change at different time scales. The main results showed that: (1) Twelve extreme climate indices (ECIs) were detected to have a significant impact on runoff changes, mainly on a 6-year time scale; (2) The R10 and Rx1day in extreme precipitation index and SU34.4 and TNx in the extreme temperature index were the main driving factors of runoff changes, which had relatively large impacts on runoff changes in high and low energy vibration regions. However, the remaining eight ECIs that passed the 0.05 confidence level showed relatively large impacts on runoff changes only in low energy vibration regions; (3) The transition of the interaction between ECIs and runoff changes in high and low time–frequency scales was related to the abrupt change characteristics of the ECIs. The correlation of abrupt change was an important reason for the emergence of highly correlated regions that trigger high and low energy vibrations; (4) As a whole, the extreme precipitation events were ahead of runoff changes at the high time–frequency scale and exhibited small lag effects at the low time–frequency scale, while extreme temperature events were mainly ahead of runoff changes. This study has effectively revealed the impact of climate factors at different scales on runoff changes, and provides a theoretical understanding for regulating and managing water resources in karst basins.
Citation: Atmosphere
PubDate: 2023-05-25
DOI: 10.3390/atmos14060927
Issue No: Vol. 14, No. 6 (2023)
- Atmosphere, Vol. 14, Pages 928: Characterization of Volatile Organic
Compounds (VOCs) from Farms Effluents: Interest of HS-SPME-GC-MS Technique
for Laboratory and Field Test
Authors: Nicolas Joguet, Lun Jing, Frank Jamois, Philippe Dumargue
First page: 928
Abstract: Livestock is an important source of volatile organic compounds (VOCs) that can cause odor nuisance and pollution. The main sources of these VOCs in livestock are effluents and their management system. In this study, the applicability of headspace-solid phase microextraction coupled with gas chromatography-mass spectrometry (HS-SPME-GC-MS) for VOC characterization in effluent samples in both laboratory and field tests was evaluated. In the laboratory test, the VOC profile of different farm effluents (cattle dung, slurry and chicken droppings) was measured as well as the influence of the presence of litter material on their release. In the field test, a comparison was made between the VOC profile of two manure pits that had undergone treatment or not to assist in effluent management. The results presented here show that the HS-SPME-GC-MS technique allows one to quantify a wide spectrum of VOCs responsible for olfactory nuisances (177 and 73 VOCs in total for the laboratory and field tests, respectively) in a simple, fast, and economic way. This technique could be further developed to monitor olfactory nuisance markers and predict the evolution of different effluent materials.
Citation: Atmosphere
PubDate: 2023-05-25
DOI: 10.3390/atmos14060928
Issue No: Vol. 14, No. 6 (2023)
- Atmosphere, Vol. 14, Pages 929: Modelling of Wildfire Susceptibility in
Different Climate Zones in Montenegro Using GIS-MCDA
Authors: Gojko Nikolić, Filip Vujović, Jelena Golijanin, Ante Šiljeg, Aleksandar Valjarević
First page: 929
Abstract: Montenegro has different influences on the weather and climate; in general, according to Köppen’s classification, there are two climate zones: warm temperate (C) and cold temperate (D). The aim of this study is to determine the susceptibility to wildfires in the Montenegrin coastal municipality of Budva and the northern municipality of Rožaje, which are located in different climatic conditions, using multicriteria GIS decision analysis (GIS-MCDA). Nine natural and anthropogenic criteria were used for the analysis. Open geospatial data were used as input data for all criteria. The assignment of weighting coefficients for the criteria in relation to wildfire susceptibility importance was based on the Analytic Hierarchy Process (AHP) and Fuzzy Analytic Hierarchy Process (F-AHP) procedures. The results for the AHP and F-AHP models were obtained using the Weighted Linear Combination (WLC) method. According to the AHP model, the very high and high category covers 80.93% of the total area in Budva and 80.65% in Rožaje. According to the F-AHP model, the very high and high category occupies 80.71% of the total area in Budva and 82.30% in Rožaje. The validation shows that the models of GIS-MCDA perform fair in both climatic zones. The proposed models, especially in the absence of geospatial data, can be a strategic and operational advantage in the development of plans and strategies for protection against wildfires.
Citation: Atmosphere
PubDate: 2023-05-25
DOI: 10.3390/atmos14060929
Issue No: Vol. 14, No. 6 (2023)
- Atmosphere, Vol. 14, Pages 930: Using Deep Learning to Identify
Circulation Patterns of Intense Rainfall in the
Beijing–Tianjing–Hebei Region
Authors: Linguo Jing, Qi Zhong, Xiaojie Li, Xiuming Wang, Lili Shen, Yong Cao
First page: 930
Abstract: The properties and distributions of precipitation are often determined by specific synoptic patterns. Hence, the objective identification of corresponding impact patterns is an important field of research for improving rain forecasting. However, the identification of the weather patterns producing intense rainfall is much more challenging. Since they are violent and local, impact patterns tend to be meso- or smaller-scale systems and are often incompletely presented or only presented in limited regions. In this paper, a deep learning network with a feature cross-fusion module, FConvNeXt, was proposed to address this difficulty and showed great potential. Four major patterns corresponding to intense rainfall in the Beijing–Tianjing–Hebei Region were studied. Statistical testing showed that FConvNeXt performed better than ConvNeXt and ResNet and that the model could identify the weak synoptic forcing type, the subtropical high-pressure type, and the low-vortex pattern with high accuracy. Furthermore, a strictly independent 2021 dataset was tested, and FConvNeXt maintained an equal if not even slightly better performance in spite of a decrease in the subtropical high-pressure type. Meanwhile, the study showed that the accuracy in identifying the upper-level trough type is the lowest for the three deep learning methods, which may be because the northeast vortex was intercepted in the limited region, making it difficult to distinguish from the shallow upper-level trough type. This study is useful for improving the fine objective of forecasting intense rainfall.
Citation: Atmosphere
PubDate: 2023-05-25
DOI: 10.3390/atmos14060930
Issue No: Vol. 14, No. 6 (2023)
- Atmosphere, Vol. 14, Pages 931: Inverse Modeling of Formaldehyde Emissions
and Assessment of Associated Cumulative Ambient Air Exposures at Fine
Scale
Authors: Eduardo P. Olaguer
First page: 931
Abstract: Among air toxics, formaldehyde (HCHO) is an important contributor to urban cancer risk. Emissions of HCHO in the United States are systematically under-reported and may enhance atmospheric ozone and particulate matter, intensifying their impacts on human health. During the 2021 Michigan-Ontario Ozone Source Experiment (MOOSE), mobile real-time (~1 s frequency) measurements of ozone, nitrogen oxides, and organic compounds were conducted in an industrialized area in metropolitan Detroit. The measured concentrations were used to infer ground-level and elevated emissions of HCHO, CO, and NO from multiple sources at a fine scale (400 m horizontal resolution) based on the 4D variational data assimilation technique and the MicroFACT air quality model. Cumulative exposure to HCHO from multiple sources of both primary (directly emitted) and secondary (atmospherically formed) HCHO was then simulated assuming emissions inferred from inverse modeling. Model-inferred HCHO emissions from larger industrial facilities were greater than 1 US ton per year while corresponding emission ratios of HCHO to CO in combustion sources were roughly 2 to 5%. Moreover, simulated ambient HCHO concentrations depended significantly on wind direction relative to the largest sources. The model helped to explain the observed HCHO concentration gradient between monitoring stations at Dearborn and River Rouge in 2021.
Citation: Atmosphere
PubDate: 2023-05-26
DOI: 10.3390/atmos14060931
Issue No: Vol. 14, No. 6 (2023)
- Atmosphere, Vol. 14, Pages 932: Turbulence with Magnetic Helicity That Is
Absent on Average
Authors: Axel Brandenburg, Gustav Larsson
First page: 932
Abstract: Magnetic helicity plays a tremendously important role when it is different from zero on average. Most notably, it leads to the phenomenon of an inverse cascade. Here, we consider decaying magnetohydrodynamic (MHD) turbulence as well as some less common examples of magnetic evolution under the Hall effect and ambipolar diffusion, as well as cases in which the magnetic field evolution is constrained by the presence of an asymmetry in the number density of chiral fermions, whose spin is systematically either aligned or anti-aligned with its momentum. In all those cases, there is a new conserved quantity: the Hosking integral. We present quantitative scaling results for the magnetic integral scale as well as the magnetic energy density and its spectrum. We also compare with cases were a magnetic version of the Saffman integral is initially finite. Rotation in MHD turbulence tends to suppress nonlinearity and thereby also inverse cascading. Finally, the role of the Hosking and magnetic Saffman integrals in shell models of turbulence is examined.
Citation: Atmosphere
PubDate: 2023-05-26
DOI: 10.3390/atmos14060932
Issue No: Vol. 14, No. 6 (2023)
- Atmosphere, Vol. 14, Pages 933: Light-Scattering Properties for Aggregates
of Atmospheric Ice Crystals within the Physical Optics Approximation
Authors: Dmitriy Timofeev, Natalia Kustova, Victor Shishko, Alexander Konoshonkin
First page: 933
Abstract: This paper presents the light-scattering matrices of atmospheric-aggregated hexagonal ice particles that appear in cirrus clouds. The aggregates consist of the same particles with different spatial orientations and numbers of these particles. Two types of particle shapes were studied: (1) hexagonal columns; (2) hexagonal plates. For both shapes, we studied compact and non-compact cases of particle arrangement in aggregates. As a result, four sets of aggregates were made: (1) compact columns; (2) non-compact columns; (3) compact plates; and (4) non-compact plates. Each set consists of eight aggregates with a different number of particles from two to nine. For practical reasons, the bullet-rosette and the aggregate of hexagonal columns with different sizes were also calculated. The light scattering matrices were calculated for the case of arbitrary spatial orientation within the geometrical optics approximation for sets of compact and non-compact aggregates and within the physical optics approximation for two additional aggregates. It was found that the light-scattering matrix elements for aggregates depend on the arrangement of particles they consist of.
Citation: Atmosphere
PubDate: 2023-05-26
DOI: 10.3390/atmos14060933
Issue No: Vol. 14, No. 6 (2023)
- Atmosphere, Vol. 14, Pages 934: Analysis of the Influence of Flood on the
L4 Combination Observation of GPS and GLONASS Satellites
Authors: Juntao Wu, Mingkun Su, Jun Gong, Lingsa Pan, Jiale Long, Fu Zheng
First page: 934
Abstract: With global warming, extreme weather such as floods and waterlogging occurs more frequently and seriously in recent years. During the flood, the surrounding environment of the GNSS (Global Navigation Satellite System) station will change as the volume of water increases. Considering the multipath error is directly relevant to the observation environment, thus, the influence of flood on the L4 combination observation (a geometry-free ionosphere-free linear combination of carrier phase) which is related to the multipath error of GPS (Global Positioning System) and GLONASS satellites is investigated in depth. In addition, the ground track repetition periods of GPS and GLONASS satellites are analyzed in the sky plot to illustrate the rationality of chosen reference day. Based on the results of the satellite sky plot, one and eight days are adopted to demonstrate the influence of flood on L4 combination observation for GPS and GLONASS satellites, respectively. Real data sets collected at the ZHNZ GNSS observation station during the flood from DOY (Day of Year) 193 to DOY 204, 2021 are used. Experimental results show that the flood has a significant impact on the L4 combination observation of GPS and GLONASS satellites, and the fluctuation of L4 under flood performs much larger than that of without flood. For GPS satellites, the maximum RMS (root mean square) increase rate of L4 under flood is approximately 186.67% on the G31 satellite. Even for the minimum RMS increase rate, it can reach approximately 23.52%, which is the G02 satellite. Moreover, the average RMS increase rate of GPS and GLONASS satellites can reach approximately 109.53% and 43.65%, respectively. In addition, the influence of rainfall and hardware device are also investigated, which can further demonstrate that the fluctuation of L4 is mainly caused by the flood but not by the rainfall and hardware device elements. Thus, based on the above results, the influence of flood on L4 observation should be taken into account during the applications of L4 used, such as the retrieval of soil moisture and vegetation water content based on GNSS L4 combination observations
Citation: Atmosphere
PubDate: 2023-05-26
DOI: 10.3390/atmos14060934
Issue No: Vol. 14, No. 6 (2023)
- Atmosphere, Vol. 14, Pages 935: An Improved S-Band Polarimetric
Radar-Based QPE Algorithm for Typhoons over South China Using 2DVD
Observations
Authors: Zeyong Guo, Sheng Hu, Guangyu Zeng, Xingdeng Chen, Honghao Zhang, Feng Xia, Jiahui Zhuang, Min Chen, Yuwen Fan
First page: 935
Abstract: Polarimetric radar data are an important tool for quantitative precipitation estimation (QPE), which is essential for monitoring and forecasting precipitation. Previous studies have shown that the drop size distribution (DSD) and polarimetric radar parameters of typhoon-induced precipitation differ significantly from those of other types of rainfall. South China is a region that frequently experiences typhoons and heavy rainfall, which can cause serious disasters. Therefore, it is critical to develop a QPE algorithm that is suitable for typhoon precipitation over South China. In this study, we constructed four simple QPE estimators, R(ZH), R(ZH, ZDR), R(KDP) and R(KDP, ZDR) based on two-dimensional video disdrometer (2DVD) DSD observations of typhoon-induced precipitation over South China in 2017–2018. We analyzed the DSD characteristics and the estimation accuracy of these four QPE estimators in the reflectivity–differential reflectivity (ZH–ZDR) space, as well as the S-band polarimetric radar (S-POL) data of seven typhoon-induced precipitation events that affected South China in 2017–2019. We used these data to quantitatively determine the optimal ranges of the estimators and establish a typhoon precipitation QPE algorithm for typhoon-induced precipitation over South China (2DVD-Typhoon). The evaluation results showed that: (1) compared to R(ZH) and R(KDP), R(ZH, ZDR) and R(KDP, ZDR) had lower performance in estimating typhoon-induced rainfall after incorporating the polarimetric parameter ZDR, as strong crosswind of the typhoon caused some bias in the raindrop-induced ZDR; (2) the 2DVD-Typhoon algorithm utilizes the respective advantages of the individual estimators to generate the best QPE results; (3) the QPE performance of 2DVD-Typhoon and the Colorado State University–Hydrometeor Identification Rainfall Optimization (CSU-HIDRO) is used as a comparison for hourly rainfall, cumulative rainfall and different rainfall intensity. The comparison shows that 2DVD-Typhoon gives a better normalized error (NE), root mean square error (RMSE) and correlation coefficient (CC), indicating its strength in rainfall estimation for typhoons over South China. The above results provide theoretical support for improving typhoon-induced rainfall monitoring and numerical weather forecasting models in South China.
Citation: Atmosphere
PubDate: 2023-05-26
DOI: 10.3390/atmos14060935
Issue No: Vol. 14, No. 6 (2023)
- Atmosphere, Vol. 14, Pages 936: ERA5 Reanalysis of Environments Conducive
to Lightning-Ignited Wildfires in Catalonia
Authors: Nicolau Pineda, Oriol Rodríguez
First page: 936
Abstract: In the climate change context, wildfires are an increasing hazard in the Mediterranean Basin, especially those triggered by lightning. Although lightning activity can be predicted with a reasonable level of confidence, the challenge remains in forecasting the thunderstorm’s probability of ignition. The present work aims to characterise the most suitable predictors to forecast lightning-ignited wildfires. Several ERA5 parameters were calculated and compared for two different samples, thunderstorm episodes that caused a wildfire (n = 961) and ordinary thunderstorms (n = 1023) that occurred in Catalonia (NE Iberian Peninsula) in the 2006–2020 period. Lightning wildfires are mostly associated with dry thunderstorms, characterised by: weak-to-moderate Mixed-Layer Convective Available Potential Energy (MLCAPE, 150–1100 J kg−1), significant Dew Point Depression at 850 hPa (DPD850, 3.3–10.1 °C), high Most-Unstable Lifted Condensation Level (MULCL, 580–1450 m) and steep 500–700 hPa Lapse Rate (LR, −7.0–−6.3 °C). Under these conditions, with relatively dry air at lower levels, thunderstorms tend to be high-based, the rain evaporating before reaching the ground and lightning occurring without significant rainfall. Specifically forecasting the probability of LIW occurrence would be of great assistance to the forest protection tactical decision-making process, preparing for “dry” thunderstorm days where multiple ignitions can be expected.
Citation: Atmosphere
PubDate: 2023-05-26
DOI: 10.3390/atmos14060936
Issue No: Vol. 14, No. 6 (2023)
- Atmosphere, Vol. 14, Pages 937: Climate Potential for Apple Growing in
Norway—Part 2: Assessment of Suitability of Heat Conditions under
Future Climate Change
Authors: Mirjam Vujadinović Mandić, Ana Vuković Vimić, Milica Fotirić Akšić, Mekjell Meland
First page: 937
Abstract: The commercial apple production in Norway is limited to the small regions along the fjords in the southwest part of the country and around lakes or near the sea in the southeast with favorable climate. Due to the rapid rate of climate change over the recent decades, it is expected that suitable heat conditions for apple growing will expand to the areas that were previously too cold. This study analyses the heat suitability of future climate (2021–2100) under the RCP8.5 scenario for 6 common apple varieties in Norway: Discovery, Gravenstein, Summerred, Aroma, Rubinstep and Elstar. Previously established heat requirement criteria (based on the temperature threshold for the full blooming and growing degree days sum between the full bloom and harvest) are applied to the temperature outputs of the regional climate models downscaled to 1 km resolution. The assessment indicates that as temperature rises, heat conditions suitable for cultivation of all 6 apple varieties will expand. According to the ensemble median value, areas with the favorable heat conditions for growing at least one of the considered apple varieties will increase 25 times in the period 2021–2040 and 60 times in the period 2041–2060, compared to the referent period 1971–2000. At the same time, areas suitable for all 6 apple varieties will increase 3 times in the first, and 3.8 times in the latter period. The favorable areas will advance from south and southeast northwards and inland in the eastern region, along the west and northwestern coastline towards higher latitudes, and along continental parts of fjords. The fastest expansion of heat suitable conditions is expected for Discovery and Gravenstein. The findings of this study are relevant for zoning apple production future potential and for strategical planning of climate change adaptation measures within the sector. Weather-related risks, such as risks from winter low temperatures, spring frost, drought and extreme precipitation were not considered.
Citation: Atmosphere
PubDate: 2023-05-26
DOI: 10.3390/atmos14060937
Issue No: Vol. 14, No. 6 (2023)
- Atmosphere, Vol. 14, Pages 938: Response Time of Vegetation to Drought in
Weihe River Basin, China
Authors: Fan, Wei, Liu, Zhou, Li, Wu, Xu
First page: 938
Abstract: Frequent droughts may have negative influences on the ecosystem (i.e., terrestrial vegetation) under a warming climate condition. In this study, the linear regression method was first used to analyze trends in vegetation change (normalized difference vegetation index (NDVI)) and drought indices (Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI)). The Pearson Correlation analysis was then used to quantify drought impacts on terrestrial vegetation in the Weihe River Basin (WRB); in particular, the response time of vegetation to multiple time scales of drought (RTVD) in the WRB was also investigated. The trend analysis results indicated that 89.77% of the area of the basin showed a significant increasing trend in NDVI from 2000 to 2019. There were also significant variations in NDVI during the year, with the highest rate in June (0.01) and the lowest rate in January (0.002). From 2000 to 2019, SPI and SPEI at different time scales in the WRB showed an overall increasing trend, which indicated that the drought was alleviated. The results of correlation analysis showed that the response time of vegetation to drought in the WRB from 2000 to 2019 was significantly spatially heterogeneous. For NDVI to SPEI, the response time of 12 months was widely distributed in the north; however, the response time of 24 months was mainly distributed in the middle basin. The response time of NDVI to SPI was short and was mainly concentrated at 3 and 6 months; in detail, the response time of 3 months was mainly distributed in the east, while a response time of 6 months was widely distributed in the west. In autumn and winter, the response time of NDVI to SPEI was longer (12 and 24 months), while the response time of NDVI to SPI was shorter (3 months). From the maximum correlation coefficient, the response of grassland to drought (SPEI and SPI) at different time scales (i.e., 6, 12, and 24 months) was higher than that of cultivated land, forestland, and artificial surface. The results may help improve our understanding of the impacts of climatic changes on vegetation cover.
Citation: Atmosphere
PubDate: 2023-05-26
DOI: 10.3390/atmos14060938
Issue No: Vol. 14, No. 6 (2023)
- Atmosphere, Vol. 14, Pages 939: Projected Future Changes in Extreme
Climate Indices over Central Asia Using RegCM4.3.5
Authors: Tugba Ozturk
First page: 939
Abstract: This work projected future extreme climate indices’ changes over Central Asia (The Coordinated Regional Climate Downscaling Experiment—CORDEX Region 8). Changes were calculated for 2071–2100 relative to 1971–2000. Climate simulations were obtained by downscaling the RegCM4.3.5 to 50 km resolution under RCP4.5 and 8.5 with HadGEM2-ES and MPI-ESM-MR. The results indicate that the Central Asian domain will experience warmer and more extreme temperatures with increasing radiative forcing. The annual lowest value of minimum daily temperature was simulated to increase remarkably, up to 8 degrees, especially in high latitudes, with a more than 12 degree increase projected over Siberia. A strong growth in the percentage of warm nights and an increase in the days of warm spells for the whole region, with a decrease in cold spell duration, are anticipated. Model results show an expected reduction of up to 30% in precipitation totals over the domain, except for the increased precipitation over Siberia, the Himalayas, and Tibetan Plateau. Extreme precipitation events are projected to have an increase of 20% over the whole domain, with an 80% increase over high topographical areas.
Citation: Atmosphere
PubDate: 2023-05-27
DOI: 10.3390/atmos14060939
Issue No: Vol. 14, No. 6 (2023)
- Atmosphere, Vol. 14, Pages 940: Quantifying the Spatio-Temporal Pattern
Differences in Climate Change before and after the Turning Year in
Southwest China over the Past 120 Years
Authors: Meng Wang, Shouyan Wang, Zhengfeng An
First page: 940
Abstract: In conjunction with Earth’s ongoing global warming, the Southwest China (SWC) region has become a fascinating case study on the control of local climate change. Moreover, an entire period of climate change may partially mask the patterns in some stages. Therefore, in this research, we investigated the spatial patterns of the significant turning years of climatic factor change, and determined the heterogeneity of the spatial patterns of climate change before and after the significant turning years. We used the long time-series of the CRU datasets (CRU_TS4.02) from 1901 to 2017 with a piecewise linear regression model to explore the significant turning-year distribution characteristics of inter-annual and inter-seasonal climate factor changes, and further describe and quantize the differences in the spatio-temporal patterns of climate factors before and after the significant turning years on the grid scale in SWC. Overall, the trends in temperature and precipitation factors in SWC were segmented over the last 120 years, with significant turning years with different regional and stepwise characteristics. In terms of timing, temperature and precipitation factors changed significantly in 1954 and 1928, respectively, and overall temporal variability (0.04 °C/(10 a) (p < 0.05), −0.48 mm/(10 a)) masked the magnitude or direction of variability (0.13 °C/(10 a) and 0.16 °C/(10 a) both at the level of p < 0.05 before the turning year, 19.56 mm/(10 a) (p < 0.05) and 1.19 mm/(10 a) after the turning year) around the watershed years. Spatially, the significant turning years were concentrated in the periods 1940–1993 (temperature) and 1910–2008 (precipitation), and the distribution pattern of the turning years was patchy and concentrated. The turning years of temperature factors were gradually delayed from east to west, and the variability of climate factors before and after the turning years exhibited significant shifts in location (e.g., temperature decreased from southeast to northwest before the turning year and increased after the turning year). After the turning year, the warming variability of the temperature factor increased, while the increasing variability of the precipitation factor decreased. Further integrated analysis revealed that the increase in variability of the climate factor after the turning year was mainly due to the increase in winter and autumn variability (0.05 °C/(10 a), 7.30 mm/(10 a) in autumn; and 0.12 °C/(10 a), 1.97 mm/(10 a) in winter). To the extent that this study provides a necessary academic foundation for efficiently unveiling the spatio-temporal variability properties of climate factors against the background of modern global climate change, more attention should be paid to the location and phase of the study.
Citation: Atmosphere
PubDate: 2023-05-27
DOI: 10.3390/atmos14060940
Issue No: Vol. 14, No. 6 (2023)
- Atmosphere, Vol. 14, Pages 941: Study of Time-Frequency Domain
Characteristics of the Total Column Ozone in China Based on Wavelet
Analysis
Authors: Chaoli Tang, Fangzheng Zhu, Yuanyuan Wei, Xiaomin Tian, Jie Yang, Fengmei Zhao
First page: 941
Abstract: Ozone is a very important trace gas in the atmosphere, it is like a “double-edged sword”. Because the ozone in the stratosphere can effectively help the earth’s organisms to avoid the sun’s ultraviolet radiation damage, the ozone near the ground causes pollution. Therefore, it is essential to explore the time-frequency domain variation characteristics of total column ozone and have a better understanding of its cyclic variation. In this paper, based on the monthly scale dataset of total column ozone (TCO) (September 2002 to February 2023) from Atmospheric Infrared Sounder (AIRS) carried by NASA’s Aqua satellite, linear regression, coefficient of variation, Mann-Kendall (M-K) mutation tests, wavelet analysis, and empirical orthogonal function decomposition (EOF) analysis were used to analyze the variation characteristics of the TCO in China from the perspectives of time domain, frequency domain, and spatial characteristics. Finally, this study predicted the future of TCO data based on the seasonal autoregressive integrated moving average (SARIMA) model in the time series algorithm. The results showed the following: (1) From 2003 to 2022, the TCO in China showed a slight downward trend, with an average annual change rate of −0.29 DU/a; the coefficient of variation analysis found that TCO had the smallest intra-year fluctuations in 2008 and the largest intra-year fluctuations in 2005. (2) Using the M-K mutation test, it was found that there was a mutation point in the total amount of column ozone in 2016. (3) Using wavelet analysis to analyze the frequency domain characteristics of the TCO, it was observed that TCO variation in China had a combination of 14-year, 6-year, and 4-year main cycles, where 14 years is the first main cycle with a 10-year cycle and 6 years is the second main cycle with a 4-year cycle. (4) The spatial distribution characteristics of the TCO in China were significantly different in each region, showing a distribution characteristic of being high in the northeast and low in the southwest. (5) Based on the EOF analysis of the TCO in China, it was found that the variance contribution rate of the first mode was as high as 52.85%, and its spatial distribution of eigenvectors showed a “-” distribution. Combined with the trend analysis of the time coefficient, this showed that the TCO in China has declined in the past 20 years. (6) The SARIMA model with the best parameters of (1, 1, 2) × (0, 1, 2, 12) based on the training on the TCO data was used for prediction, and the final model error rate was calculated as 1.34% using the mean absolute percentage error (MAPE) index, indicating a good model fit.
Citation: Atmosphere
PubDate: 2023-05-27
DOI: 10.3390/atmos14060941
Issue No: Vol. 14, No. 6 (2023)
- Atmosphere, Vol. 14, Pages 942: Synoptic Weather Patterns and Atmospheric
Circulation Types of PM2.5 Pollution Periods in the Beijing-Tianjin-Hebei
Region
Authors: Shijie Gu, Shuai Wu, Luoqi Yang, Yincui Hu, Bing Tian, Yan Yu, Ning Ma, Pengsong Ji, Bo Zhang
First page: 942
Abstract: The variation of PM2.5 concentration in the atmosphere is closely related to the variation in weather patterns. The change in weather pattern is accompanied by the corresponding change in atmospheric circulation characteristics. It is necessary to explore the relationship between PM2.5 concentration changes and atmospheric circulation characteristics during pollution periods. In this paper, Lamb-Jenkinson objective classification method is applied to classify daily atmospheric circulation. The pollution periods are calculated and the atmospheric circulation variation rule is obtained. Combined with the physical parameter field (humidity, potential temperature, and potential height), a typical pollution period is analyzed. Additionally, the influence of atmospheric circulation type variation on PM2.5 concentration and transport channel during the pollution period was obtained. The results show that atmospheric circulation types in the study period are dominated by A-type (anticyclonic), N-type (north), and NE-type (northeast), indicating obvious seasonal differences, and the proportion of C-type (cyclonic) circulation was increased significantly in summer. During the pollution period analysis from 2 to 4 January 2019, atmospheric circulation type changed from N-type to NE-type (northeast), the wind direction changed from southeast wind, and the change of pressure gradient was consistent with the trend of the wind field. Moreover, the physical parameter field assisted in verifying the process of the pollution period from the conducive to the accumulation of PM2.5 to conducive to the deposition of pollutants and external transport. The research results would provide theoretical support for PM2.5 prediction during the pollution period and also supply a theoretical and technical basis for the establishment of ecological compensation standards for air pollution and atmospheric environmental control.
Citation: Atmosphere
PubDate: 2023-05-27
DOI: 10.3390/atmos14060942
Issue No: Vol. 14, No. 6 (2023)
- Atmosphere, Vol. 14, Pages 943: Spatio-Temporal Change Pattern
Investigation of PM2.5 in Jiangsu Province with MODIS Time Series Products
Authors: Jieqiong Luo, Meiqin Che
First page: 943
Abstract: In the last decade, the spatio-temporal patterns of PM2.5 on various scales, ranging from global, continent, and country to regional levels, has been the focus of considerable studies. However, these studies on spatio-temporal variability have concentrated primarily on changes in the spatial distribution patterns of regional PM2.5 concentrations and ignored temporal characteristics at a local site from a heterogeneous surface, such as local variability, persistence, and stability of PM2.5 exposure. Understanding the temporal characteristics of PM2.5 concentration changes at the local scale will help determine the local impacts of PM2.5, such as local exposure risk and vulnerability to PM2.5. This study aims to reveal the local characteristics of temporal variation at the scale of a prefecture-level city and its distinct-varying patterns from those at the provincial scale by using the annual satellite-derived PM2.5 concentration product from 2000 to 2015. The evolutionary trends, stability, and persistence of annual changes were discovered with a set of time series analysis methods, such as linear regression analysis + F-test, coefficient of variation method, and Hurst index. This study uses PM2.5 product data for a total of 16 years, from 2000 to 2015, and uses time series analysis methods, such as Theil–Sen median trend analysis + Mann–Kendall test, one-dimensional linear regression analysis + F-test, coefficient of variation method, and Hurst index, to reveal the temporal variation characteristics and spatial patterns of PM2.5 in Jiangsu Province. The results show that the increasing trends or slopes of annual averaged PM2.5 concentrations in Jiangsu Province are not consistent at the prefecture-level city scale, but they are consistent in northern, central and southern Jiangsu at a larger upward trend since 2000. The areas with significant increasing trends are concentrated in Xuzhou and Lianyungang and other northern cities. From the viewpoint of variability, the areas in medium and high variability are mainly aggregated in the areas north of the Yangtze River. According to the combination of persistence analysis and trend analysis, future variation in PM2.5 concentrations indicates an inverse persistence for an increasing trend, meaning the air quality decline in Jiangsu will slow.
Citation: Atmosphere
PubDate: 2023-05-27
DOI: 10.3390/atmos14060943
Issue No: Vol. 14, No. 6 (2023)
- Atmosphere, Vol. 14, Pages 844: Parametric Enhancement of a
Window-Windcatcher for Enhanced Thermal Comfort and Natural Ventilation
Authors: Laith M. Obeidat, Odi Fawwaz Alrebei, Shouib Nouh Ma’bdeh, Tamer Al-Radaideh, Abdulkarem I. Amhamed
First page: 844
Abstract: Window-windcatchers, a passive ventilation method, have been shown to improve ventilation and enhance thermal comfort. Preliminary characterization of a novel window-windcatcher has been undertaken in a previous work, but no relationship had been identified between the actual ventilation rate (Qact), the wind velocity (VTw) and crucial design parameters such as the fins angle (ϴ)). In this paper, the relationship that quantifies how the window-windcatcher’s performance depends on VTw and ϴ was determined. Additionally, for the first time, the ventilation performance of the window-windcatcher was optimized by studying the effects of ϴ and the fins-wall distance (DW−f) through a Computational Fluid Dynamics parametric study (ANSYS) . In this optimization approach, the angle ϴ and the distance DW−f corresponding to the maximum actual-to-required ventilation rate were found to be 80° and 45 cm, respectively. The actual ventilation rate increased by approximately 13.2% compared with the baseline design of the windcatcher (ϴ and DW−f equal to 40° and 45 cm, respectively); this corresponds to an increase of approximately 8.6% in the actual-to-required ventilation rate, according to the ASHRAE standards.
Citation: Atmosphere
PubDate: 2023-05-09
DOI: 10.3390/atmos14050844
Issue No: Vol. 14, No. 5 (2023)
- Atmosphere, Vol. 14, Pages 845: Laser Attenuation and Ranging Correction
in the Coal Dust Environment Based on Mie Theory and Phase Ranging
Principle
Authors: Ben Li, Shanjun Mao, Hong Zhang
First page: 845
Abstract: The inadequate ventilation and complex environments in underground coal mines lead to a high concentration of dust particles. As a result, the health of the miners and the accuracy of laser rangefinder measurements are endangered. It is crucial to enhance the laser rangefinder’s efficiency to mitigate health risks and reduce labor intensity. In this study, we propose a laser power attenuation model and a ranging correction model to address the issues of laser power attenuation and inaccurate ranging in coal dust environments. The proposed models are based on theoretical analysis and practical experiments, and both are dependent on the dust particle size (<250 μm) and mass concentration. Firstly, we assessed the factors that caused laser power attenuation and demonstrated that our proposed model could accurately predict them (maximum residual of 0.06). Secondly, we obtained the connection between the attenuation coefficient and dust concentration by applying the Lambert–Beer law. Lastly, we established the ranging correction model by collecting laser wavelength information. The outcomes show that the root mean square error of the corrected values ranges between 0.27 and 0.47 mm. To summarize, our suggested model and correction technique can efficiently enhance the precision of laser rangefinder measurements, thus improving underground work in coal mines.
Citation: Atmosphere
PubDate: 2023-05-09
DOI: 10.3390/atmos14050845
Issue No: Vol. 14, No. 5 (2023)
- Atmosphere, Vol. 14, Pages 846: Artificial Periodic Irregularities and
Temperature of the Lower Thermosphere
Authors: Nataliya V. Bakhmetieva, Gennadiy I. Grigoriev, Ilia N. Zhemyakov, Elena E. Kalinina
First page: 846
Abstract: The results of temperature measurements in the lower thermosphere at altitudes of 90–130 km by the method of resonant scattering of radio waves on artificial periodic inhomogeneities (APIs) of the ionospheric plasma are presented. These inhomogeneities are created when the ionosphere is exposed to powerful HF radio emission. The temperature profile was obtained from measurements of the relaxation time of the API scattered signal. The data processes and the method of the temperature determination are given in detail. The height and temporal resolutions of the API technique are of the order of 1 km and 15 s, respectively, making it possible to study both fast and slow processes in the lower thermosphere. Large temperature variability at altitudes of 90–130 km during the day and from day to day, due to the propagation of atmospheric waves, has been confirmed. The temporal variations of the atmospheric parameters take place with periods from 15 min to some hours. There are often height profiles of the temperature with the wave-like variations and with the vertical scale of about 4–10 km. The irregular temperature profiles were observed above 100 km.
Citation: Atmosphere
PubDate: 2023-05-09
DOI: 10.3390/atmos14050846
Issue No: Vol. 14, No. 5 (2023)
- Atmosphere, Vol. 14, Pages 847: A Cluster Analysis Approach for Nocturnal
Atmospheric Boundary Layer Height Estimation from Multi-Wavelength Lidar
Authors: Zhongmin Zhu, Hui Li, Xiangyang Zhou, Shumin Fan, Wenfa Xu, Wei Gong
First page: 847
Abstract: The atmospheric boundary layer provides useful information about the accumulation and diffusion of pollutants. As a fast method, remote sensing techniques are used to retrieve the atmospheric boundary layer height (ABLH). Atmospheric detection lidar has been widely applied for retrieving the ABLH by providing information on the vertical distribution of aerosols. However, these previous algorithms that rely on gradient change are susceptible to residual layers. Contrary to the use of gradient change to retrieve ABLH, in this paper, we propose using a cluster analysis approach through multifunction lidar remote sensing techniques due to its increasing availability. The clustering algorithm for multi-wavelength lidar data can be divided into two parts: characteristic signal selection and selection of the classifier. First, since the separability of each type of signal is different, careful selection of the input characteristic signal is important. We propose using Fourier transform for all the observed signals; the most suitable characteristic signal can be determined based on the dispersion degree of the signal in the frequency domain. Then, the performances of four common classifiers (K-means method, Gaussian mixture model, hierarchical cluster method (HCM), and density-based spatial clustering of applications with noise) are evaluated by comparing with the radiosonde measurements from June 2015 to June 2016. The results show that the performance of the HCM classifier is the best under all states (R2 = 0.84 and RMSE = 0.18 km). The findings obtained here offer insight into ABLH remote sensing technology.
Citation: Atmosphere
PubDate: 2023-05-09
DOI: 10.3390/atmos14050847
Issue No: Vol. 14, No. 5 (2023)
- Atmosphere, Vol. 14, Pages 848: New Developments in Climate Change, Air
Pollution, Pollen Allergy, and Interaction with SARS-CoV-2
Authors: Gennaro D’Amato, Isabella Annesi-Maesano, Benedetta Biagioni, Andrea Lancia, Lorenzo Cecchi, Maria Concetta D’Ovidio, Maria D’Amato
First page: 848
Abstract: In recent years, the environmental impacts of climate change have become increasingly evident. Extreme meteorological events are influenced by climate change, which also alter the magnitude and pattern of precipitations and winds. Climate change can have a particularly negative impact on respiratory health, which can lead to the emergence of asthma and allergic respiratory illnesses. Pollen is one of the main components of the atmospheric bioaerosol and is able to induce allergic symptoms in certain subjects. Climate change affects the onset, length, and severity of the pollen season, with effects on pollen allergy. Higher levels of carbon dioxide (CO2) can lead to enhanced photosynthesis and a higher pollen production in plants. Pollen grains can also interact with air pollutants and be affected by thunderstorms and other extreme events, exacerbating the insurgence of respiratory diseases such as allergic rhinitis and asthma. The consequences of climate change might also favor the spreading of pandemics, such as the COVID-19 one.
Citation: Atmosphere
PubDate: 2023-05-09
DOI: 10.3390/atmos14050848
Issue No: Vol. 14, No. 5 (2023)
- Atmosphere, Vol. 14, Pages 849: Remote Detection of Different Marine Fuels
in Exhaust Plumes by Onboard Measurements in the Baltic Sea Using
Single-Particle Mass Spectrometry
Authors: Ellen Iva Rosewig, Julian Schade, Johannes Passig, Helena Osterholz, Robert Irsig, Dominik Smok, Nadine Gawlitta, Jürgen Schnelle-Kreis, Jan Hovorka, Detlef Schulz-Bull, Ralf Zimmermann, Thomas W. Adam
First page: 849
Abstract: Ship emissions are a major cause of global air pollution, and in particular, emissions from the combustion of bunker fuels, such as heavy fuel oil (HFO), show strong impacts on the environment and human health. Therefore, sophisticated measurement techniques are needed for monitoring. We present here an approach to remotely investigating ship exhaust plumes through onboard measurements from a research vessel in the Baltic Sea. The ship exhaust plumes were detected from a distance of ~5 km by rapid changes in particle number concentration and a variation in the ambient particle size distribution utilizing a condensation particle counter (CPC) and a scanning mobility particle sizer (SMPS) instrument. Ambient single particles in the size range of 0.2–2.5 µm were qualitatively characterized with respect to their chemical signature by single-particle mass spectrometry (SPMS). In particular, the high sensitivity of the measurement method for transition metals in particulate matter (PM) was used to distinguish between the different marine fuels. Despite the high complexity of the ambient aerosol and the adverse conditions at sea, the exhaust plumes of several ships could be analyzed by means of the online instrumentation.
Citation: Atmosphere
PubDate: 2023-05-10
DOI: 10.3390/atmos14050849
Issue No: Vol. 14, No. 5 (2023)
- Atmosphere, Vol. 14, Pages 850: Evaluation of PBL Parameterization Schemes
in WRF Model Predictions during the Dry Season of the Central Amazon Basin
Authors: José Antonio Mantovani Júnior, José Antonio Aravéquia, Rayonil Gomes Carneiro, Gilberto Fisch
First page: 850
Abstract: Planetary Boundary Layer (PBL) parameterization schemes are employed to handle subgrid-scale processes on atmospheric models, playing a key role in accurately representing the atmosphere. Recent studies have shown that PBL schemes are particularly fundamental to the depiction of PBL height (PBLH), especially over the Amazon. In the present study, we investigated the performance of PBL schemes on the representation of meteorological variables, turbulent fluxes, PBL vertical structures, and PBLH over the central Amazon basin under dry conditions, taking advantage of observations from the Observations and Modeling of the Green Ocean Amazon campaign (GoAmazon2014/5) for validation and evaluation. Numerical experiments were carried out within the WRF model using eight PBL schemes for two dry periods from 2014 (typical year) and 2015 (El-Niño year), and results from the 1-km resolution domain were directly compared to hourly in situ observations. In general, all PBL schemes present good performance to reproduce meteorological variables, with nonlocal (local) PBL schemes producing better performance in the 2014 (2015) study period. All PBL schemes in general overestimate (>100%) daytime turbulent fluxes. Thermodynamic (daytime) vertical structures are better predicted than mechanical (nocturnal) ones. The local MYNN2.5 scheme showed the overall best performance for PBLH prediction, mainly at night.
Citation: Atmosphere
PubDate: 2023-05-10
DOI: 10.3390/atmos14050850
Issue No: Vol. 14, No. 5 (2023)
- Atmosphere, Vol. 14, Pages 851: Spatiotemporal Assessment of Atmospheric
Pollutants in Yancheng City, Eastern Coastal City of China
Authors: Boni Wang, Chunting Zhang, Liang Huang, Gu Zhang, Xinyi Yuan, Ruan Yao, Min Zhang
First page: 851
Abstract: Atmospheric environmental pollution has become a critical issue in eastern coastal cities in China, so a broad understanding of its spatiotemporal characteristics is of importance to develop public policies. In this study, hourly data of ρ(PM2.5), ρ(PM10), ρ(NO2), ρ(SO2), ρ(O3) and φ(CO) of five different types of national air quality monitoring sites from 2016 to 2020 were analyzed, combined with the change of meteorological elements in the same period in Yancheng, which was a rapidly developed eastern coastal city in China. The results indicated that the pollutant concentrations except for ρ(O3) was low in summer and high in winter, decreasing year by year from 2016 to 2020. The proportion of moderately and heavily contaminated days in the whole year was decreasing from 80 days in 2016 to 52 days in 2020, and the days with good quality increased from 284 days in 2016 to 311 days in 2020. ρ(O3) was the highest in spring and the lowest in winter, increasing slightly year by year. The variation of ρ(PM2.5), ρ(PM10), ρ(NO2), ρ(SO2) and φ(CO) showed a double-peak type, reaching the peak value at 8:00–10:00 and 20:00–22:00, corresponding to the early and evening rush hours. ρ(PM2.5), ρ(PM10) and φ(CO) on the weekend were higher than on weekdays, while an insignificant difference of ρ(NO2), ρ(O3) and ρ(SO2) was found between weekdays and the weekend. Wind direction played a key role in the variation of pollutant concentration in the Yancheng urban area, and the correlation analysis indicated that ρ(PM2.5) and ρ(PM10) were highly correlated to wind direction. Temperature was positively correlated to ρ(O3), while air pressure was significantly negatively correlated to ρ(O3). Relative humidity was negatively correlated to ρ(PM2.5), ρ(PM10), ρ(NO2), ρ(SO2) and φ(CO), while air pressure was positively correlated with these pollutants.
Citation: Atmosphere
PubDate: 2023-05-10
DOI: 10.3390/atmos14050851
Issue No: Vol. 14, No. 5 (2023)
- Atmosphere, Vol. 14, Pages 852: Traits of Adaptive Outdoor Thermal Comfort
in a Tropical Urban Microclimate
Authors: Chng Saun Fong, Suneja Manavvi, Radhakrishnan Shanthi Priya, Logaraj Ramakreshnan, Nik Meriam Sulaiman, Nasrin Aghamohammadi
First page: 852
Abstract: Urban heat islands (UHIs) are negatively impacting the quality of the urban environment and outdoor thermal comfort (OTC) levels, which have raised concerns regarding their impact on urban health and well-being. Understanding of OTC level is crucial, particularly in tropical cities with year-round high temperatures and humidity. A study was conducted in Kuala Lumpur (KL), Malaysia, to determine the OTC level in a selected urban area through microclimate measurements and questionnaire surveys with 1157 respondents. Over half of the urban dwellers reported thermal discomfort, with a high perceived OTC level, indicating strong thermal adaptive behaviours among the urban dwellers despite the physiological stress. Confounding factors such as urban morphology, land cover and human activity patterns also influence the OTC level in the tropical city. The findings emphasize the need for interventions to improve the urban environment and promote better outdoor thermal comfort for city dwellers through measures such as green infrastructure, UHI mitigation and increasing public awareness.
Citation: Atmosphere
PubDate: 2023-05-10
DOI: 10.3390/atmos14050852
Issue No: Vol. 14, No. 5 (2023)
- Atmosphere, Vol. 14, Pages 853: Prediction of PM10 Concentration in
Malaysia Using K-Means Clustering and LSTM Hybrid Model
Authors: Noratiqah Mohd Ariff, Mohd Aftar Abu Bakar, Han Ying Lim
First page: 853
Abstract: Following the rapid development of various industrial sectors, air pollution frequently occurs in every corner of the world. As a dominant pollutant in Malaysia, particulate matter PM10 can cause highly detrimental effects on human health. This study aims to predict the daily average concentration of PM10 based on the data collected from 60 air quality monitoring stations in Malaysia. Building a forecasting model for each station is time-consuming and unrealistic; therefore, a hybrid model that combines the k-means clustering technique and the long short-term memory (LSTM) model is proposed to reduce the number of models and the overall model training time. Based on the training set, the stations were clustered using the k-means algorithm and an LSTM model was built for each cluster. Then, the prediction performance of the hybrid model was compared with the univariate LSTM model built independently for each station. The results show that the hybrid model has a comparable prediction performance to the univariate LSTM model, as it gives the relative percentage difference (RPD) less than or equal to 50% based on at least two accuracy metrics for 43 stations. The hybrid model can also fit the actual data trend well with a much shorter training time. Hence, the hybrid model is more competitive and suitable for real applications to forecast air quality.
Citation: Atmosphere
PubDate: 2023-05-11
DOI: 10.3390/atmos14050853
Issue No: Vol. 14, No. 5 (2023)
- Atmosphere, Vol. 14, Pages 854: Interdecadal Variation of Summer Extreme
Heat Events in the Beijing–Tianjin–Hebei Region
Authors: Yanan Liang, Junzhi Zhang, Ji Wang, Tiejun Xie
First page: 854
Abstract: Extreme heat events are frequent in the Beijing–Tianjin–Hebei (BTH) region due to global warming and accelerated urbanization. While previous studies have analyzed the trend of extreme heat events in the Beijing–Tianjin–Hebei (BTH) region, the interdecadal changes of these events remain unclear. Therefore, this study aims to analyze the interdecadal temporal and spatial characteristics of summer extreme heat events in the BTH region using daily mean and maximum temperature datasets from 174 stations over the period 1979–2020. The results are shown as follows: (1) From 1979 to 2020, extreme heat events showed an overall upward trend in the BTH region. There were similarities in the changes in the extreme maximum temperature (TXx) and the number of high-temperature days (Htd) between different generations, and both were low until the mid-1990s. (2) In terms of the spatial pattern, TXx and Htd both showed the spatial distribution characteristics of being high in the south and low in the north. Extreme heat events in the BTH region were mainly concentrated in Beijing City, Tianjin City, and the eastern region of Hebei, and the TXx increase in most areas reached 1.5–2.0 °C. (3) The number of high-temperature days (Htd) increased significantly in the background of global warming, especially in Beijing, Tianjin, and Shijiazhuang Cities. (4) Extreme heat events in the BTH region mainly occurred in June and July, and the interdecadal changes showed a decreasing trend in June and an increasing trend in July. A high proportion of Htd was concentrated in Northern Hebei Province in July.
Citation: Atmosphere
PubDate: 2023-05-11
DOI: 10.3390/atmos14050854
Issue No: Vol. 14, No. 5 (2023)
- Atmosphere, Vol. 14, Pages 855: Compositional Difference and Health Risk
Assessment of Polycyclic Aromatic Hydrocarbons over the Coal Spontaneous
Combustion Zone
Authors: Feng Yu, Yang Yu, Ning Ai, Juanqin Gao, Chenghui Wang, Fan Huang
First page: 855
Abstract: In this study, the U.S. Environmental Protection Agency prioritized polycyclic aromatic hydrocarbons (PAHs), associated pollution level, and health risks were assessed in a typical coal spontaneous combustion zone in the Rujigou coal mine in Northwestern China. This study used gas chromatography-mass spectrometry (GC-MS) to detect the chemical composition, spatial variation, distribution profiles, impact of coal spontaneous combustion, and health risks of PAHs. The entire study area is divided into three zones according to different features: the spontaneous combustion zone (C-zone), the living zone (L-zone), and the non-spontaneous combustion zone (N-zone). The results showed that: (1) the highest concentrations were measured in the C-zone, and the average concentrations of PAHs in the C-zone, N-zone, and L-zone were 13.28 ng·m−3, 9.56 ng·m−3, and 7.67 ng·m−3, respectively. (2) The PAHs of the study area were mainly composed of three ring to five ring PAHs. (3) EPA positive matrix factorization (PMF) analysis of qualitative source apportionment of PAHs showed that chemical production was the major source of atmospheric PAHs in all three zones, followed by coal combustion. (4) The inhalation of PAHs showed higher potential cancer risk for children than for adults, and the impact of coal combustion in the C-zone was much greater than the other zone. The adverse health impacts associated with PAH exposure indicates the need for mitigation measures of pollution control in this region.
Citation: Atmosphere
PubDate: 2023-05-11
DOI: 10.3390/atmos14050855
Issue No: Vol. 14, No. 5 (2023)
- Atmosphere, Vol. 14, Pages 856: Cardiovascular and Respiratory Health
Effects of Fine Particulate Matters (PM2.5): A Review on Time Series
Studies
Authors: Wan Rozita Wan Mahiyuddin, Rohaida Ismail, Noraishah Mohammad Sham, Nurul Izzah Ahmad, Nik Muhammad Nizam Nik Hassan
First page: 856
Abstract: Ambient air pollution remains one of the most important risk factors for health outcomes. In recent years, there has been a growing number of research linking particulate matter (PM) exposure with adverse health effects, especially on cardiovascular and respiratory systems. The objective of this review is to examine the range and nature of studies on time series analysis of health outcomes affected by PM2.5 across a broad research area. A literature search was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) extension for scoping review framework through a strategic search of PubMed and ScienceDirect online databases for articles from January 2016 to January 2021. Articles were first screened by their titles and abstracts. Then two reviewers independently reviewed and evaluated the full text of the remaining articles for eligibility. Of the 407 potentially relevant studies, 138 articles were included for final analysis. There was an increasing trend in publications from 2016 to 2019 but a decreasing trend in the year 2020. Most studies were conducted in Eastern and South-Eastern Asia (69.6%), Europe and Northern America (14.5%) and Latin America and the Caribbean (8.7%), with the majority coming from high- and upper-middle-income countries (95.6%). The main methodology used was Generalized Additive Model (GAM) with Poisson distribution (74.6%). Morbidity was the most common health outcome studied (60.1%), with vulnerable groups (64.5%) often included. The association between PM2.5 and health effects was stronger for respiratory diseases compared to cardiovascular diseases. In short-term studies (less than 7 years), respiratory diseases showed higher risks compared to cardiovascular. However, in long-term studies (7 years and more), cardiovascular showed higher risks.
Citation: Atmosphere
PubDate: 2023-05-11
DOI: 10.3390/atmos14050856
Issue No: Vol. 14, No. 5 (2023)
- Atmosphere, Vol. 14, Pages 857: Cooling Effect of Trees with Different
Attributes and Layouts on the Surface Heat Island of Urban Street Canyons
in Summer
Authors: Shaojun Yan, Tailong Zhang, Yu Wu, Chu Lv, Feng Qi, Yangen Chen, Xiaohua Wu, Yamei Shen
First page: 857
Abstract: In recent years, the impact of surface heat islands in urban street canyons has become increasingly apparent. However, the research on the use of trees to mitigate surface heat islands remains limited. To address this gap, this study combines experiments and simulations to analyze the cooling effect of trees on surface temperatures under varying timeframes and layouts in an east–west street canyon. The results reveal that the temperature of the road decreases by 10–15 °C, which is 2–4 times greater than that on the south side. Moreover, at 5:00 p.m. in the afternoon, the cooling effect on the south side is 10.3 °C, which is twice that of the north side. In practical planning and design, the diameter of the tree canopy should be maximized, and trees with leaf-area densities greater than 1.5 m2/m3 should be selected. Additionally, the layout of trees should be optimized to maximize the tree canopy coverage. These findings have important implications for optimizing plant selection and placement in street canyons.
Citation: Atmosphere
PubDate: 2023-05-11
DOI: 10.3390/atmos14050857
Issue No: Vol. 14, No. 5 (2023)
- Atmosphere, Vol. 14, Pages 858: Projecting Bioclimatic Change over the
South-Eastern European Agricultural and Natural Areas via
Ultrahigh-Resolution Analysis of the de Martonne Index
Authors: Ioannis Charalampopoulos, Fotoula Droulia, Ioannis X. Tsiros
First page: 858
Abstract: The changing climate is closely related to changes in the bioclimate. This research deals with the present bioclimate and its projected evolution over the entirety of the natural and agricultural lands of south-eastern Europe and individual countries (Bulgaria, Greece, Kosovo, N. Macedonia, Romania, and Serbia). For this purpose, an ultrahigh spatial resolution of the de Martonne bioclimatic index pattern was elaborated and analysed for the first time. The survey is performed over the reference period (1981–2010) and future time frames (2011–2040; 2041–2070; 2071–2100) under SSP370 and SSP585 emission scenarios. On a territorial level, both natural and agricultural areas appear as highly impacted by the future changes of bioclimate; the highest xerothermic trend is expected to influence the latter areas, mostly in 2071–2100 and under the higher emission scenario. The natural areas will face an expansion in the semidry class from 0.9% (of the total area) during the reference period to 5.6% during 2071–2100 under the RCP8.5 scenario as the dominant extremely humid class falls from 53.5% to 32.9% for the same periods and scenario. On the other hand, agricultural areas will face a more intense xerothermic alteration going from 4.9% to 17.7% for the semidry class and from 41.1% to 23.5% for the dominant very humid class for the same periods and scenario. This study presents the spatial statistics per country for the selected scenarios and periods to provide information for stakeholders. This study’s results highlight the necessity for intensifying adaptation plans and actions aiming at the feasibility of agricultural practices and the conservation of natural areas.
Citation: Atmosphere
PubDate: 2023-05-11
DOI: 10.3390/atmos14050858
Issue No: Vol. 14, No. 5 (2023)
- Atmosphere, Vol. 14, Pages 859: A Study on Radiological Hazard Assessment
for Jordan Research and Training Reactor
Authors: Mohammad Talafha, Sora Kim, Kyung-Suk Suh
First page: 859
Abstract: Numerical simulations of atmospheric dispersion and dose assessment were performed for the Jordan Research and Training Reactor (JRTR) to evaluate its radiological effects on surrounding population and the environment. A three-dimensional atmospheric dispersion model was applied to investigate the behavior of the radionuclides released into the air, and a dose assessment model was used to estimate the radiological impact on the population residing in nearby cities around the JRTR. Considering full core meltdown an accidental scenario, most of the source term was assumed to be released from the JRTR. Simulations were performed to calculate the air and deposition concentrations of radioactive materials for July 2013 and January 2014. The monthly averaged values of concentrations, depositions, and dose rates were analyzed to identify the most harmful effects in each month. The results showed that relatively harmful effects occurred in January 2014, and the total annual dose rate was estimated to be approximately 1 mSv outside the 10 km radius from JRTR. However, the impact of a nuclear accident is not as severe as it might seem, as the affected area is not highly populated, and appropriate protective measures can significantly reduce the radiation exposure. This study provides useful information for emergency preparedness and response planning to mitigate the radiological consequences of a nuclear accident at the JRTR.
Citation: Atmosphere
PubDate: 2023-05-11
DOI: 10.3390/atmos14050859
Issue No: Vol. 14, No. 5 (2023)
- Atmosphere, Vol. 14, Pages 860: The Effects of Drought in the Huaibei
Plain of China Due to Climate Change
Authors: Ousmane Badji, Yonghua Zhu, Haishen Lü, Kanon Guédet Guédé, Tingxing Chen, Abdoulaye Oumarou, Kouassi Bienvenue Mikael Onan Yao, Sika Brice
First page: 860
Abstract: Damage from climate change is widespread throughout the world. This change has brought about calamities, the most prevalent of which is the emergence of numerous droughts which are increasingly threatening human lives. In this paper, we studied the spatial and temporal variations of drought under the effect of climate change in the Huaibei Plain, which is a very important agricultural zone in China. Drought has attracted increasing attention in research due to its heavy impact on agriculture, the environment, livelihood, and food security. The SPEI (Standardized Precipitation Evapotranspiration Index) has been used in this study to express and identify drought events in the Huaibei Plain due to climate change. A general circulation model (GCM), HadGEM2-AO, which was the most appropriate for the study area’s precipitation simulation, and three Representative Concentration Pathways (RCP), RCP 2.6, RCP 4.5, and RCP 8.5, were used to analyze and compare the drought effect for the baseline (1985–2017) and the future climate scenarios (2025–2090). At 3 and 6 months, the SPEI successfully detects agricultural drought in temporal and spatial variation. However, according to the analysis, more severe agricultural drought events are foreseen in the future than in the baseline because of climate change. SPEI performed better than SPI in detecting drought in the baseline and simulated data due to increased evapotranspiration. Between the SPEI-3 and SPEI-6, the Pearson coefficient correlation reveals a positive association. The Mann-Kendall test was used to cover the two studied periods in order to establish the drought trend. Both decreasing and increasing trends, in different timescales, were detected by Sen’s Slope in the baseline and future periods with all RCPs.
Citation: Atmosphere
PubDate: 2023-05-11
DOI: 10.3390/atmos14050860
Issue No: Vol. 14, No. 5 (2023)
- Atmosphere, Vol. 14, Pages 861: Climate Variability and Trends in Imotski,
Croatia: An Analysis of Temperature and Precipitation
Authors: Adrijana Vrsalović, Ivo Andrić, Ognjen Bonacci, Omer Kovčić
First page: 861
Abstract: This paper examines the long-term changes in temperature and precipitation in the karst region of Imotski, Croatia, which is of particular interest due to its abundance of karst phenomena. This study analyses temperatures and precipitation on monthly and annual scales at two climatological stations in the region, Imotski and Ričice. Linear regression, the Theil–Sen estimator (β), and the Mann–Kendall test were used to determine the trends and statistical significance. The homogeneity of the data was checked using the Standard Normal Homogeneity Test (SNHT), and the F-test and t-test were used to test the significance of the mean shift between the two subseries. Additionally, the coefficient of variability, standardized rainfall anomaly, and precipitation concentration index were employed to analyze the precipitation variability. The study found a statistically significant (p < 0.05) upward trend in the mean (β = 0.0437) and maximum (β = 0.0590) annual air temperature at the Imotski station and the mean (β = 0.0387) annual temperature at the Ričice station. The SNHT test showed a statistically significant (p < 0.05) shift in the mean annual temperatures after 2007 and maximum annual temperatures after 1998 at the Imotski station. Similarly, a statistically significant (p < 0.05) shift in the mean annual temperatures after 2011 and the maximum annual temperatures after 1998 was found at the Ričice station. A seasonal distribution of precipitation is observed at both the Ričice and Imotski stations, with a downward trend (β = −2.7693) at Ričice and an upward trend (β = 6.0575) at Imotski; however, neither trend is statistically significant (p > 0.05). An increase in the intensity of dry periods and the occurrence of extreme events was also noted. The climatological analysis, conducted for the first time in this area, is a crucial step toward understanding local climate patterns and making informed decisions toward sustainable development and adaptation strategies.
Citation: Atmosphere
PubDate: 2023-05-11
DOI: 10.3390/atmos14050861
Issue No: Vol. 14, No. 5 (2023)
- Atmosphere, Vol. 14, Pages 862: Physicochemical Assessment of the Road
Vehicle Traffic Pollution Impact on the Urban Environment
Authors: Marcel Rusca, Tiberiu Rusu, Simona Elena Avram, Doina Prodan, Gertrud Alexandra Paltinean, Miuta Rafila Filip, Irina Ciotlaus, Petru Pascuta, Tudor Andrei Rusu, Ioan Petean
First page: 862
Abstract: Vehicle traffic pollution requires complex physicochemical analysis besides emission level measuring. The current study is focused on two campaigns of emissions measurements held in May and September 2019 in Alba Iulia City, Romania. There was found a significant excess of PM2.5 for all measuring points and PM10 for the most circulated points during May, along with significant VOC and CO2 emissions. September measurements reveal threshold excess for all PM along with increased values for VOC and CO2 emissions. These are the consequences of the complex environmental interaction of the traffic. Street dust and air-suspended particle samples were collected and analyzed to evidence the PM2.5 and PM10 sources. Physicochemical investigation reveals highly mineralized particulate matter: PM2.5 fractions within air-suspended particle samples predominantly contain Muscovite, Kaolinite, and traces of Quartz and Calcite, while PM10 fractions within air-suspended particle samples predominantly contain Quartz and Calcite. These mineral fractions originate in street dust and are suspended in the atmosphere due to the vehicles’ circulation. A significant amount of soot was found as small micro-sized clusters in PM2.5 and fine micro-spots attached over PM10 particles, as observed by Mineralogical Optical Microscopy (MOM) and Fourier Transformed Infrared Spectroscopy (FTIR). GC-MS analysis found over 53 volatile compounds on the investigated floating particles that are related to the combustion gases, such as saturated alkanes, cycloalkanes, esters, and aromatic hydrocarbons. It proves a VOC contamination of the measured particulate matters that make them more hazardous for the health. Viable strategies for vehicle traffic-related pollutants mitigation would be reducing the street dust occurrence and usage of modern catalyst filters of the combustion gas exhausting system.
Citation: Atmosphere
PubDate: 2023-05-11
DOI: 10.3390/atmos14050862
Issue No: Vol. 14, No. 5 (2023)
- Atmosphere, Vol. 14, Pages 863: Intensive Silvopastoral Systems Mitigate
Enteric Methane Emissions from Cattle
Authors: Gustavo Flores-Coello, Juan H. Hernández-Medrano, Juan Ku-Vera, Daniel Diaz, Francisco J. Solorio-Sánchez, Lucero Sarabia-Salgado, Francisco Galindo
First page: 863
Abstract: Assessments of the efficiency of grazing systems, in terms of productivity and ecological sustainability, are necessary in view of the increased demand for animal protein. In this study, the methane (CH4) emissions (sniffer methodology), dry matter (DM) yield, paddock chemical composition (AOAC and Van Soest methods), nutrient intake (dry matter, DMI; crude protein, CPI; metabolizable energy, MEI), daily milk yield (DMY), body condition score (BCS), and body weight (BW) of cattle, in intensive silvopastoral systems (ISPSs) and monoculture systems (MSs), in the tropics of Mexico were evaluated. In the ISPS, CH4 emissions (18% less) and DMY were lower than in the MS. Cows from MSs tend to disperse across higher values of CH4 emissions per kg of DMI, as well as higher milk production, while cows from the ISPS were dispersed over a higher intake (DMI, CPI, and MEI) and lower CH4 emissions. There were no differences between systems in paddock DM yield, chemical composition, cows’ BCS, and BW, regardless of whether it was the dry (April to May) and rainy (September to October) season. Based on the results obtained in this study, ISPSs contribute to the mitigation of methane emissions in cattle; forage and animal production variables in both systems were similar, with a lower use of imported inputs in the ISPS.
Citation: Atmosphere
PubDate: 2023-05-12
DOI: 10.3390/atmos14050863
Issue No: Vol. 14, No. 5 (2023)
- Atmosphere, Vol. 14, Pages 864: Chemical Characteristics and Source
Apportionment of PM2.5 in Western Industrial Region of Jinan
Authors: Jian Guo, Haiyong Wang, Shanjun Liu, Zhanshan Wang
First page: 864
Abstract: In order to obtain the chemical composition characteristics and source apportionment of PM2.5 in a western industrial region of Jinan, manual sampling and analysis of PM2.5 in Pingyin County was conducted during 2019. The results showed that the total concentration of 29 species of PM2.5 was 53.8 μg·m−3. The NO3− concentration (14.6 ± 14.2 μg·m−3) was the highest, followed by OC (9.3 ± 5.5 μg·m−3), SO42− (9.1 ± 6.4 μg·m−3) and NH4+ (8.1 ± 6.8 μg·m−3). Concentrations of OC, NO3− and SO42− were highest in winter and lowest in summer. The concentration of NH4+ was highest in winter and lowest in spring. The annual SOR and NOR were 0.30 ± 0.14 and 0.21 ± 0.12, respectively. SO2 emission and conversion ratio was highest in winter, leading to the highest SO42− concentration. SO2 emission in summer was low, but the conversion ratio was high. NOR in winter and autumn were close and higher than spring and summer. The high NOR in autumn caused a higher NO3− concentration compared with that in spring and summer. The average concentration of SOC during 2019 was 2.8 ± 1.9 μg·m−3, accounting for 30% of OC. The PMF results showed that coal emission accounted for 36.5% of PM2.5 concentration, followed by mobile sources (32.6%), industry emission (17.4%), dust emission (7.1%) and other emissions (6.4%).
Citation: Atmosphere
PubDate: 2023-05-12
DOI: 10.3390/atmos14050864
Issue No: Vol. 14, No. 5 (2023)
- Atmosphere, Vol. 14, Pages 865: Sniffing Drones: A Promising Solution for
Measuring Railroad Emissions in Urban Environments
Authors: Felipe Baglioli, Ricardo H. M. Godoi
First page: 865
Abstract: Locomotive emissions from railroads can particularly impact air pollution, making it crucial to understand their impacts on human health and the environment and develop strategies to reduce them. The potential of drone technology equipped with a “sniffing” system for detecting air pollution emissions is promising and can be a valuable tool for assessing dynamic emissions. This research utilized sensor-equipped drones to measure gaseous emissions from cargo and passenger trains on a railway in Curitiba, Brazil. Reference equipment evaluated the accuracy of NO2, SO2, and O3 concentrations. The results showed that before the passage of trains, the average SO2 concentration was 20 µg/m³, with a maximum concentration of 110 µg/m³ detected during transit. The average increase in NO2 concentrations was from 30 µg/m³ to 120 µg/m³, and the average increase in O3 concentrations was from 80 µg/m³ to 135 µg/m³. The vertical profiles were evaluated before and after the passage of locomotives, indicating an accumulation of pollutants above the railroad. These findings demonstrate the potential of sniffing drones to measure railroad emissions in urban environments. They also highlight the need to regulate emissions from diesel-powered locomotives to minimize atmospheric pollution and its negative impact on public health in emerging and developing countries.
Citation: Atmosphere
PubDate: 2023-05-12
DOI: 10.3390/atmos14050865
Issue No: Vol. 14, No. 5 (2023)
- Atmosphere, Vol. 14, Pages 866: A Hurricane Initialization Scheme with
4DEnVAR Satellite Ozone and Bogus Data Assimilation (SOBDA) and Its
Application: Case Study
Authors: Yin Liu
First page: 866
Abstract: The aim of this study is to joint assimilate the ozone product from the satellite Atmospheric Infrared Sounder (AIRS) and bogus data using the four-dimensional ensemble-variational (4DEnVar) method, and demonstrate the potential benefits of this initialization technique in improving hurricane forecasting through a case study. Firstly, the quality control scheme is employed to enhance the ozone product quality from the satellite AIRS; a bogus sea level pressure (SLP) at the hurricane center is constructed simultaneously based on Fujita’s mathematical model for subsequent assimilation. Secondly, a 4DEnVar satellite ozone and bogus data assimilation (SOBDA) model is established, incorporating an observation operator of satellite ozone that utilizes the relationship between satellite ozone and potential vorticity (PV) from the lower level of 400 hPa to the upper level of 50 hPa. Finally, several comparative experiments are performed to assess the influence of assimilating satellite ozone and/or bogus data, the 4DEnVAR method and four-dimensional variational (4D-Var) method, and ensemble size on hurricane prediction. It is found that assimilating satellite ozone and bogus data with the 4DEnVar method concurrently brings about significant alterations to the initial conditions (ICs) of the hurricane vortex, resulting in a more homogeneous and deeper vortex with a larger, warmer, and more humid core as opposed to assimilating only one type of data. As the duration of integration increases, the initial perturbations in the upper levels gradually propagate downwards, giving rise to significant disparities in the hurricane prediction when satellite ozone and/or bogus information is incorporated. The results demonstrate that utilizing the 4DEnVar approach to assimilate both satellite ozone and bogus data leads to the maximum enhancement in reducing track error and central SLP error of hurricane simulation throughout the entire 72 h forecasting period, compared to assimilating a single dataset. Furthermore, comparative experiments have indicated that the performance of 4DEnVar SOBDA in hurricane forecasting is influenced by the ensemble size. Generally, selecting an appropriate number of ensemble members can not only effectively improve the accuracy of hurricane prediction but can also significantly reduce the demand for computational resources relative to the 4D-Var method. This study can also serve as an advantageous technical reference for numerical applications of ozone products from other satellites and hurricane initialization.
Citation: Atmosphere
PubDate: 2023-05-12
DOI: 10.3390/atmos14050866
Issue No: Vol. 14, No. 5 (2023)
- Atmosphere, Vol. 14, Pages 867: Air Pollutants and Their Impact on Chronic
Diseases—A Retrospective Study in Bucharest, Romania
Authors: Beatrice Mahler, Dragoș Băiceanu, Traian Constantin Panciu, Radu Marian Florea, Ana Luiza Iorga, Marcin Gnat, Cornelia Florina German, Simona Pârvu, Dorel Paraschiv, Daniela Manea, Mihaela Mihai, Elmira Ibraim, Bogdan Timar, Florin Dumitru Mihălțan
First page: 867
Abstract: Air pollution is a serious problem in Romania, with the country ranking 13th among the most polluted countries in Europe in the 2021 World Air Quality Report. Despite the recognized impact of pollutants on health, there has been a lack of large-scale studies conducted in Romania. This study investigated the impact of air pollutants on patients with chronic respiratory, cardiovascular, cerebrovascular, or metabolic diseases in Bucharest and its metropolitan area from 20 August 2018 to 1 June 2022. The daily limit values for particulate matter PM10 and PM2.5 were exceeded every month, especially during the cold season, with a decrease during the COVID-19 pandemic restrictions. A significant statistical correlation was found between the monthly average values of PM2.5 and PM10 and hospitalizations for respiratory and cardiovascular diseases. A 10 µg/m3 increase in monthly average values resulted in a 40–60% increase in admissions for each type of pathology, translating to more than 2000 admissions for each pathology for the study period. This study highlights the urgent need for national and local measures to ensure a cleaner environment and enhance public health in Romania according to international regulations.
Citation: Atmosphere
PubDate: 2023-05-12
DOI: 10.3390/atmos14050867
Issue No: Vol. 14, No. 5 (2023)
- Atmosphere, Vol. 14, Pages 868: Strength Deterioration of Earthen Sites
Loess Solidified by Calcined Ginger Nuts under Dry–Wet and
Freeze–Thaw Cycles
Authors: Qifeng Li, Bing Dang, Dandan Li, Xiaoying Hu
First page: 868
Abstract: Earthen sites are a kind of constructure with significant historical and cultural value. However, the destruction of earthen sites caused by erosion occurs frequently. The solidification of calcined ginger nuts can improve the strength of the soil so that it can be used to protect the earthen sites. However, the strength degradation of solidified soil by calcined ginger nuts after dry–wet and freeze–thaw cycles is unclear. To reveal the deterioration pattern of solidified soil strength, the effects of its dosage and cycle number on the strength of solidified soil were analyzed through shear strength, dry–wet cycle, and freeze–thaw cycle tests. The results showed that the solidified soil strength decreased first and increased with dosage increase. With the number of dry–wet cycles increasing, the strength of the plain loess decreased rapidly and gradually turned flat. The strength loss of solidified soil was small in the dry–wet process. With freeze–thaw cycle numbers increasing, the strength of the plain loess decreased first and then tended to be flat, the strength of solidified soil decreased first and then increased slightly, and the change in the strength had a clear inflection point. With the increasing dosage, freeze–thaw cycle numbers corresponding to the inflection point were significantly reduced. These results indicate that calcined ginger nuts could enhance the resistance of earthen sites loess to dry–wet and freeze–thaw cycles.
Citation: Atmosphere
PubDate: 2023-05-14
DOI: 10.3390/atmos14050868
Issue No: Vol. 14, No. 5 (2023)
- Atmosphere, Vol. 14, Pages 869: A Hybrid Autoformer Network for Air
Pollution Forecasting Based on External Factor Optimization
Authors: Kai Pan, Jiang Lu, Jiaren Li, Zhenyi Xu
First page: 869
Abstract: Exposure to air pollution will pose a serious threat to human health. Accurate air pollution forecasting can help people to reduce exposure risks and promote environmental pollution control, and it is also an extremely important part of smart city management. However, the current deep-learning-based models for air pollution forecasting usually focus on prediction accuracy improvement without considering the model interpretability. These models usually fail to explain the complex relationships between prediction targets and external factors (e.g., ozone concentration (O3), wind speed, temperature variation, etc.) The relationships between variables in air pollution time series prediction problems are very complex, with intricate relationships between different types of variables, often with nonlinear multivariate dependencies. To address these problems mentioned above, we proposed a hybrid autoformer network with a genetic algorithm optimization to predict air pollution temporal variation as well as establish interpretable relationships between pollutants and external variables. Furthermore, an elite variable voting operator was designed to better filter out more important external factors such as elite variables, so as to perform a more refined search for elite variables. Moreover, we designed an archive storage operator to reduce the effect of neural network model initialization on the search for external variables. Finally, we conducted comprehensive experiments on the Ma’anshan air pollution dataset to verify the proposed model, where the prediction accuracy was improved by 2–8%, and the selection of model influencing factors was more interpretable.
Citation: Atmosphere
PubDate: 2023-05-14
DOI: 10.3390/atmos14050869
Issue No: Vol. 14, No. 5 (2023)
- Atmosphere, Vol. 14, Pages 870: A Parametric Model of Elliptic Orbits for
Annual Evolutions of Northern Hemisphere Stratospheric Polar Vortex and
Their Interannual Variability
Authors: Yueyue Yu, Jie Sun, Michael Secor, Ming Cai, Xinyue Luo
First page: 870
Abstract: The year-to-year varying annual evolutions of the stratospheric polar vortex (SPV) have an important downward impact on the weather and climate from winter to summer and thus potential implications for seasonal forecasts. This study constructs a parametric elliptic orbit model for capturing the annual evolutions of mass-weighted zonal momentum at 60° N (MU) and total air mass above the isentropic surface of 400 K (M) over the latitude band of 60–90° N from 1 July 1979 to 30 June 2021. The elliptic orbit model naturally connects two time series of a nonlinear oscillator. As a result, the observed coupling relationship between MU and M associated with SPV as well as its interannual variations can be well reconstructed by a limited number of parameters of the elliptic orbit model. The findings of this study may pave a new way for short-time climate forecasts of the annual evolutions of SPV, including its temporal evolutions over winter seasons as well as the spring and fall seasons, and timings of the sudden stratospheric warming events by constructing its elliptic orbit in advance.
Citation: Atmosphere
PubDate: 2023-05-14
DOI: 10.3390/atmos14050870
Issue No: Vol. 14, No. 5 (2023)
- Atmosphere, Vol. 14, Pages 871: Spatiotemporal Precipitation Trends and
Associated Large-Scale Teleconnections in Northern Pakistan
Authors: Ansa Rebi, Azfar Hussain, Ishtiaq Hussain, Jianhua Cao, Waheed Ullah, Haider Abbas, Safi Ullah, Jinxing Zhou
First page: 871
Abstract: The effects of climate change are unparalleled in magnitude, ranging from changing weather patterns that endanger food production to increasing sea levels that increase the likelihood of catastrophic flooding. Therefore, determining the extent of such variations on regional and local scales is imperative. We used monthly precipitation data from 25 meteorological stations in northern Pakistan (NP) to document the observed changes in seasonal and annual precipitation. The station density in the NP is small and unevenly distributed; therefore, ERA-5 reanalysis data were used to supplement the observed dataset to assess the spatial trends in NP. The non-parametric Mann–Kendall (MK), Sen’s Slope estimator (SSE), and Sequential Mann–Kendall (SQMK) tests were performed to assess the trends. In addition, the wavelet analysis technique was used to determine the association of precipitation with various oceanic indices from 1960 to 2016. Results indicate that maximum precipitation was shown in the annual and summer seasons. In NP, annual, winter, spring, and summer precipitation declined, while an increase in autumn was observed at a rate of 0.43 mm/decade between 1989 and 2016. The spatial trends for observed and ERA-5 reanalysis datasets were almost similar in winter, spring, and autumn; however, some disagreement was observed in both datasets in the summer and annual precipitation trends in NP during 1960–2016. Between 1989 and 2016, summer and annual precipitation increased significantly in Region III. However, seasonal and annual precipitation decreased in NP between 1960 and 2016. Moreover, there were no prominent trends in annual precipitation until the mid-1980s, but an apparent increase from 1985 onwards. Annual precipitation increased in all elevations except at the 500–1000 m zone. The ENSO (El Niño–Southern Oscillation) shared notable interannual coherences among all indices above 16–64 months. Inter-decadal coherence with the ENSO, AO (Arctic Oscillation), and PDO (Pacific Decadal Oscillation) in NP for 128 months and above. Generally, AO, AMO (Atlantic Multidecadal Oscillation), and NAO (North Atlantic Oscillation) exhibited less coherence with precipitation in NP. The regression of seasonal and annual precipitation revealed that winter and spring precipitation levels had higher linear regression with the AO and ENSO, respectively, while both the AO and ENSO also dominated at the annual scale. Similarly, the IOD and PDO indices had a higher influence in summer precipitation. The findings may help water resource managers and climate researchers develop a contingency plan for better water resource management policies in the face of changing climate change in Pakistan, particularly in NP.
Citation: Atmosphere
PubDate: 2023-05-15
DOI: 10.3390/atmos14050871
Issue No: Vol. 14, No. 5 (2023)
- Atmosphere, Vol. 14, Pages 872: Formation Mechanisms of the
“5·31” Record-Breaking Extreme Heavy Rainfall Process
in South China in 2021
Authors: Fangli Chen, Huiqi Li, Sheng Hu, Shuai Jiang, Jiaojiao Li, Ruoting Wu
First page: 872
Abstract: Based on the fifth-generation European Center for Medium-Range Weather Forecasts reanalysis data (ERA5), the real-time observation data from weather stations, and the radar products in Guangdong Province, we analyze the precipitation properties and formation mechanisms of the “5·31” extreme heavy rainfall process with record-breaking 3-h accumulated rainfall in South China during 2021. The results show that the extreme heavy rainfall process is caused by the joint actions of weather systems such as a weak upper-level short-wave trough, a surface stationary front, and a low-level southwesterly jet. Before the heavy precipitation process, there is large precipitable water content and deep warm clouds, which provides a potential for the occurrence and development of the heavy rainfall process in Longhua Town of Longmen County and its surrounding areas. Simultaneously, the low-level southwesterly jet provides abundant warm-wet water vapor for the heavy rainfall area. The vertical atmospheric environmental conditions, such as strong horizontal temperature gradient, high convective available potential energy, high-temperature difference between 850 hPa and 500 hPa, and low convective inhibition, maintain for a long duration in the heavy rainfall area, which are favorable for the occurrence and development of high-efficiency convective precipitation caused by water vapor condensation due to the uplift of low-level warm-wet airflows. The combined effects of the enhanced low-level southwesterly airflow, the stationary front, the mesoscale surface convergence line generated by cold pool outflows, the terrain influence, and the train effect of the precipitation echoes make heavy precipitation near Longhua last longer and stronger than other areas, leading to the extreme heavy rainfall with the record-breaking 3-h accumulated rainfall in Longhua.
Citation: Atmosphere
PubDate: 2023-05-16
DOI: 10.3390/atmos14050872
Issue No: Vol. 14, No. 5 (2023)
- Atmosphere, Vol. 14, Pages 873: Driving Forces on the Distribution of
Urban Ecosystem’s Non-Point Pollution Reduction Service
Authors: Chengji Shu, Kaiwei Du, Baolong Han, Zhiwen Chen, Haoqi Wang, Zhiyun Ouyang
First page: 873
Abstract: In the context of increasing urbanization and worsening environmental pollution, nonpoint source pollution during high-frequency rainfall has become a major ecological problem that endangers residents in cities. This study takes Shenzhen as an example. On the basis of a large number of soil sample test data, and combined with relevant environmental variables, it has drawn the high-resolution, high-precision spatial distribution maps of soil attributes within the city. In addition, this paper combines the revised universal soil loss equation and the GeoDetector model to evaluate the supply capacity of nonpoint source reduction services in the city’s ecological space and the main driving factors of spatial distribution characteristics for different types of land. The study found that increasing soil point density and combining environmental variables can help improve the accuracy of spatial mapping for soil attributes. The ME, MSE, ASE, RMSE, and RMSSE of spatial mapping all meet the accuracy evaluation criteria and are better than many existing studies; the spatial distribution characteristics of soil attributes and nonpoint source reduction services show significant differences among the whole city, secondary administrative regions, and different types of land; the GeoDetector results show that among the three main types of land use (forested land, industrial land, and street town residential land), topographic factors, habitat-quality factors, and ecosystem types have the greatest impact on the spatial differentiation characteristics of nonpoint source reduction services. Among climate factors, only precipitation factors have the greatest impact on the spatial differentiation characteristics of services. Facing the above factors, the q-values calculated by the GeoDetector are all higher than 10%. The results of this study can provide information for making better decisions on regional ecological system management and soil protection and on restoration work aimed at improving nonpoint source reduction services.
Citation: Atmosphere
PubDate: 2023-05-16
DOI: 10.3390/atmos14050873
Issue No: Vol. 14, No. 5 (2023)
- Atmosphere, Vol. 14, Pages 874: Modeling of Organic Aerosol in Seoul Using
CMAQ with AERO7
Authors: Hyeon-Yeong Park, Sung-Chul Hong, Jae-Bum Lee, Seog-Yeon Cho
First page: 874
Abstract: The Community Multiscale Air Quality (CMAQ) model with the 7th generation aerosol module (AERO7) was employed to simulate organic aerosol (OA) in Seoul, Korea, for the year 2016. The goal of the present study includes the 1-year simulation of OA using WRF-CMAQ with recently EPA-developed AERO7 with pcVOC (potential VOC from combustion) scale factor revision and analysis of the seasonal behavior of OA surrogate species in Seoul. The AERO7, the most recent version of the aerosol module of the CMAQ model, includes a new secondary organic aerosol (SOA) species, pcSOA (potential SOA from combustion), to resolve the inherent under-prediction problem of OA. The AERO7 classified OA into three groups: primary organic aerosol (POA), anthropogenic SOA (ASOA), and biogenic SOA (BSOA). Each OA group was further classified into 6~15 individual OA surrogate species according to volatility and oxygen content to model the aging of OA and the formation of SOA. The hourly emissions of POA and SOA precursors were compiled and fed into the CMAQ to successfully simulate seasonal variations of OA compositions and ambient organic-matter to organic-carbon ratios (OM/OC). The model simulation showed that the POA and ASOA were major organic groups in the cool months (from November to March) while BSOA was a major organic group in the warm months (from April to October) in Seoul. The simulated OM/OCs ranged from 1.5~2.1 in Seoul, which agreed well with AMS measurements in Seoul in May 2016.
Citation: Atmosphere
PubDate: 2023-05-16
DOI: 10.3390/atmos14050874
Issue No: Vol. 14, No. 5 (2023)
- Atmosphere, Vol. 14, Pages 875: Fog Intermittency and Critical Behavior
Authors: Kelly Y. Huang, Gabriel G. Katul, Thomas J. Hintz, Jesus Ruiz-Plancarte, Qing Wang, Harindra J. S. Fernando
First page: 875
Abstract: The intermittency of fog occurrence (the switching between fog and no-fog) is a key stochastic feature that plays a role in its duration and the amount of moisture available. Here, fog intermittency is studied by using the visibility time series collected during the month of July 2022 on Sable Island, Canada. In addition to the visibility, time series of air relative humidity and turbulent kinetic energy, putative variables akin to the formation and breakup conditions of fog, respectively, are also analyzed in the same framework to establish links between fog intermittency and the underlying atmospheric variables. Intermittency in the time series is quantified with their binary telegraph approximations to isolate clustering behavior from amplitude variations. It is shown that relative humidity and turbulent kinetic energy bound many stochastic features of visibility, including its spectral exponent, clustering exponent, and the growth of its block entropy slope. Although not diagnostic, the visibility time series displays features consistent with Pomeau–Manneville Type-III intermittency in its quiescent phase duration PDF scaling (−3/2), power spectrum scaling (−1/2), and signal amplitude PDF scaling (−2). The binary fog time series exhibits properties of self-organized criticality in the relation between its power spectrum scaling and quiescent phase duration distribution.
Citation: Atmosphere
PubDate: 2023-05-17
DOI: 10.3390/atmos14050875
Issue No: Vol. 14, No. 5 (2023)
- Atmosphere, Vol. 14, Pages 876: Comprehensive Analysis and Greenhouse Gas
Reduction Assessment of the First Large-Scale Biogas Generation Plant in
West Africa
Authors: Haoran Chen, Qian Xu, Shikun Cheng, Ting Wu, Tong Boitin, Sunil Prasad Lohani, Heinz-Peter Mang, Zifu Li, Xuemei Wang
First page: 876
Abstract: More than 500 million people will be added to Africa’s cities by 2040, marking the largest urbanization in history. However, nonrenewable fossil energy sources are inadequate to meet Africa’s energy needs, and their overexploitation leads to intensified global warming. Fortunately, Africa has a huge potential for biomass energy, which will be an important option for combating climate change and energy shortage. In this study, we present a typical large-scale biogas plant in Burkina Faso, West Africa (Ouagadougou Biogas Plant, OUA), which is the first large-scale biogas generation plant in West Africa. The primary objective of OUA is to treat human feces, and it serves as a demonstration plant for generating electricity for feed-in tariffs. The objectives of this study are to assess the greenhouse gas reduction capacity and economic, environmental, and social benefits of OUA and to analyze the opportunities and challenges of developing biogas projects in Africa. As a result, the net economic profit of the OUA biogas plant is approximately USD 305,000 per year, with an anticipated static payback period of 14.5 years. The OUA plant has the capacity to treat 140,000 tons of human feces and 3000 tons of seasonal mixed organic waste annually, effectively reducing greenhouse gas emissions by 5232.61 tCO2eq, improving the habitat, and providing over 30 local jobs. Finally, the development of biogas projects in Africa includes advantages such as suitable natural conditions, the need for social development, and domestic and international support, as well as challenges in terms of national policies, insufficient funding, technical maintenance, and social culture.
Citation: Atmosphere
PubDate: 2023-05-17
DOI: 10.3390/atmos14050876
Issue No: Vol. 14, No. 5 (2023)
- Atmosphere, Vol. 14, Pages 877: Identification Method of Source Term
Parameters of Nuclear Explosion Based on GA and PSO for Lagrange-Gaussian
Puff Model
Authors: Yang Zheng, Yuyang Wang, Longteng Wang, Xiaolei Chen, Lingzhong Huang, Wei Liu, Xiaoqiang Li, Ming Yang, Peng Li, Shanyi Jiang, Hao Yin, Xinliang Pang, Yunhui Wu
First page: 877
Abstract: Many well-established models exist for predicting the dispersion of radioactive particles that will be generated in the surrounding environment after a nuclear weapon explosion. However, without exception, almost all models rely on accurate source term parameters, such as DELFIC, DNAF-1, and so on. Unlike nuclear experiments, accurate source term parameters are often not available once a nuclear weapon is used in a real nuclear strike. To address the problems of unclear source term parameters and meteorological conditions during nuclear weapon explosions and the complexity of the identification process, this article proposes a nuclear weapon source term parameter identification method based on a genetic algorithm (GA) and a particle swarm optimization algorithm (PSO) by combining real-time monitoring data. The results show that both the PSO and the GA are able to identify the source term parameters satisfactorily after optimization, and the prediction accuracy of their main source term parameters is above 98%. When the maximum number of iterations and population size of the PSO and GA were the same, the running time and optimization accuracy of the PSO were better than those of the GA. This study enriches the theory and method of radioactive particle dispersion prediction after a nuclear weapon explosion and is of great significance to the study of environmental radioactive particles.
Citation: Atmosphere
PubDate: 2023-05-17
DOI: 10.3390/atmos14050877
Issue No: Vol. 14, No. 5 (2023)
- Atmosphere, Vol. 14, Pages 878: Review on Source Profiles of Volatile
Organic Compounds (VOCs) in Typical Industries in China
Authors: Shuangshuang Wang, Jie Zhang, Yan Zhang, Liwei Wang, Zhongxue Sun, Hailing Wang
First page: 878
Abstract: The source profile of volatile organic compounds (VOCs) is essential for establishing reactivity- and toxicity-based emission inventories and developing effective air pollution control strategies. In this paper, the establishment of VOC source profiles and the VOC emission characteristics are reviewed in the petrochemical, solvent use, and chemical industries, and the most up-to-date profiles of the three industries in China are compiled via necessary adjustment and reconstruction of the test data from the literature. Alkanes dominated and OVOCs were often neglected in the overall petrochemical industry and refined processes. They accounted for 60.6% and 3.2% in the merged profiles. Aromatics and OVOCs dominated in the industrial solvent use industry. OVOCs were the most prevalent in the printing and dyeing industries, furniture manufacturing industries, and automobile coating process, whereas aromatics were major contributors of the total VOCs in metal surface coating, shipping coating, and other surface coating industries in the merged profiles. A wide range of products and limited profile studies were obtained in chemical industry, and the compositions of VOCs varied significantly in the production of 30 products in the merged profile. The future research directions of VOC source profiles are discussed, mainly focusing on the sampling, establishment, and evaluation of VOC profiles.
Citation: Atmosphere
PubDate: 2023-05-17
DOI: 10.3390/atmos14050878
Issue No: Vol. 14, No. 5 (2023)
- Atmosphere, Vol. 14, Pages 879: Future Ship Emission Scenarios with a
Focus on Ammonia Fuel
Authors: Daniel A. Schwarzkopf, Ronny Petrik, Josefine Hahn, Leonidas Ntziachristos, Volker Matthias, Markus Quante
First page: 879
Abstract: Current efforts by the International Maritime Organization (IMO) to decarbonize the shipping sector have gained momentum, although the exact path to achieve this goal is currently unclear. However, it can be safely assumed that alternative cleaner and zero-carbon fuels will be key components in the strategy. In this work, three ship emission scenarios for 2025, 2040, and 2050 were developed that cover the area of the North and Baltic Seas. They aim at a fundamental transition in the usage of marine fuels towards ammonia as the mainly used fuel in 2050, via an intermediate step in 2040 with liquefied natural gas as the main fuel. Additionally, expected trends and developments for the shipping sector were implemented, i.e., a fleet growth by vessel size and number. Efficiency improvements were included that are in accordance with the Energy Efficiency Design Index of the IMO. The scenarios were created using a novel method based on modifications to a virtual shipping fleet. The vessels in this fleet were subject to decommission and renewal cycles that adapt them to the scenario’s target year. Emissions for this renewed shipping fleet were calculated with the Modular Ship Emission Modeling System (MoSES). With respect to ammonia engine technology, two cases were considered. The first case deals with compression ignition engines and marine gas oil as pilot fuel, while the second case treats spark ignition engines and hydrogen as the pilot fuel. The first case is considered more feasible until 2050. Reductions with the first case in 2050 compared to 2015 were 40% for CO2 emissions. However, CO2 equivalents were only reduced by 22%, with the difference mainly resulting from increased N2O emissions. NOX emissions were reduced by 39%, and different PM components and SO2 were between 73% and 84% for the same target year. The estimated NH3 slip from ammonia-fueled ships in the North and Baltic Seas was calculated to be 930 Gg in 2050. For the second ammonia engine technology that is considered more advanced, emission reductions were generally stronger and ammonia emissions smaller.
Citation: Atmosphere
PubDate: 2023-05-17
DOI: 10.3390/atmos14050879
Issue No: Vol. 14, No. 5 (2023)
- Atmosphere, Vol. 14, Pages 880: Chemical Characterization and Source
Apportionment of PM10 Using Receptor Models over the Himalayan Region of
India
Authors: Nikki Choudhary, Akansha Rai, Jagdish Chandra Kuniyal, Priyanka Srivastava, Renu Lata, Monami Dutta, Abhinandan Ghosh, Supriya Dey, Sayantan Sarkar, Sakshi Gupta, Sheetal Chaudhary, Isha Thakur, Archana Bawari, Manish Naja, Narayanasamy Vijayan, Abhijit Chatterjee, Tuhin Kumar Mandal, Sudhir Kumar Sharma, Ravindra Kumar Kotnala
First page: 880
Abstract: This study presents the source apportionment of coarse-mode particulate matter (PM10) extracted by 3 receptor models (PCA/APCS, UNMIX, and PMF) at semi-urban sites of the Indian Himalayan region (IHR) during August 2018–December 2019. In this study, water-soluble inorganic ionic species (WSIIS), water-soluble organic carbon (WSOC), carbon fractions (organic carbon (OC) and elemental carbon (EC)), and trace elements of PM10 were analyzed over the IHR. Nainital (62 ± 39 µg m−3) had the highest annual average mass concentration of PM10 (average ± standard deviation at 1 σ), followed by Mohal Kullu (58 ± 32 µg m−3) and Darjeeling (54 ± 18 µg m−3). The annual total ∑WSIIS concentration order was as follows: Darjeeling (14.02 ± 10.01 µg m−3) > Mohal-Kullu (13.75 ± 10.21 µg m−3) > Nainital (10.20 ± 6.30 µg m−3), contributing to 15–30% of the PM10 mass. The dominant secondary ions (NH4+, SO42−, and NO3−) suggest that the study sites were strongly influenced by anthropogenic sources from regional and long-range transport. Principal component analysis (PCA) with an absolute principal component score (APCS), UNMIX, and Positive Matrix Factorization (PMF) were used for source identification of PM10 at the study sites of the IHR. All three models showed relatively similar results of source profiles for all study sites except their source number and percentage contribution. Overall, soil dust (SD), secondary aerosols (SAs), combustion (biomass burning (BB) + fossil fuel combustion (FFC): BB+FFC), and vehicular emissions (VEs) are the major sources of PM10 identified by these models at all study sites. Air mass backward trajectories illustrated that PM10, mainly attributed to dust-related aerosols, was transported from the Thar Desert, Indo-Gangetic Plain (IGP), and northwestern region of India (i.e., Punjab and Haryana) and Afghanistan to the IHR. Transported agricultural or residual burning plumes from the IGP and nearby areas significantly contribute to the concentration of carbonaceous aerosols (CAs) at study sites.
Citation: Atmosphere
PubDate: 2023-05-17
DOI: 10.3390/atmos14050880
Issue No: Vol. 14, No. 5 (2023)
- Atmosphere, Vol. 14, Pages 881: Potential Vorticity Generation in Breaking
Gravity Waves
Authors: Michael L. Waite, Nicholas Richardson
First page: 881
Abstract: Potential vorticity (PV) is an important quantity in stratified flows because it is conserved following the flow in the absence of forcing and viscous and diffusive effects. However, as shown by previous work for unstratified turbulence, viscosity and diffusion, when present, are not purely dissipative and can create potential vorticity even when none is present initially. In this work, we use direct numerical simulations to investigate the viscous and diffusive generation of potential vorticity and potential enstrophy (integrated square PV) in stratified turbulence. Simulations are initialized with a two-dimensional standing internal gravity wave, which has no potential vorticity apart from some low-level random noise; as a result, all potential vorticity and enstrophy comes from viscous and diffusive effects. Significant potential enstrophy is found when the standing wave breaks, and the maximum potential enstrophy increases with increasing Reynolds number. The mechanism for the initial PV generation is spanwise diffusion of buoyancy perturbations, which grow as the standing wave three-dimensionalizes, into the direction of spanwise vorticity. The viscous and diffusive terms responsible are small-scale and are sensitive to under-resolution, so high resolution is required to obtain robust results.
Citation: Atmosphere
PubDate: 2023-05-18
DOI: 10.3390/atmos14050881
Issue No: Vol. 14, No. 5 (2023)
- Atmosphere, Vol. 14, Pages 882: Research on Promotion Pathways for
Zero-Emission Medium- and Heavy-Duty Trucks: A Case Study of Hainan Island
Authors: Chunxiao Hao, Yunshan Ge, Jindong Liang, Zhuoshi He, Zhihui Huang, Guangyu Dou
First page: 882
Abstract: Promoting the use of zero-emission vehicles is an important measure for reducing pollutant and carbon dioxide emissions from medium- and heavy-duty trucks (MHDTs). This study took Hainan Island as an example. Based on big data such as industrial layout and traffic flow, it clarified that the main channels of freight transportation on Hainan Island are concentrated in the northern region, including the surrounding areas of Haikou; the important ports of Haikou, Yangpu, and Basuo; and Chengmai and Tunchang counties. Furthermore, pathways for the promotion of zero-emission MHDTs are proposed, which can reduce exhaust emissions by 1549 tons of NOx, 62 tons of particulate matter (PM), and 3.60 million tons of CO2 by 2030. Compared with the vehicle type categorization plan, the spatial layout plan can achieve higher emission reduction benefits in the medium term (2025). In addition, in conjunction with existing policies and planning requirements, this study also puts forward policy suggestions for the promotion of zero-emission MHDTs.
Citation: Atmosphere
PubDate: 2023-05-18
DOI: 10.3390/atmos14050882
Issue No: Vol. 14, No. 5 (2023)
- Atmosphere, Vol. 14, Pages 883: Two Case Studies of the Northwestern
Argentinean Low: With and without a Coupled Transient Trough
Authors: Josefina M. Arraut, Maurício R. Rocha, Enio P. Souza, Júlia Amanda Nanini
First page: 883
Abstract: The Northwestern Argentinean Low (NAL) intensifies the zonal component of the geopotential gradient to its east, intensifying the meridional wind and moisture flow from the tropics to the subtropics contibuting importantly to the South American Low-Level Jet and the Chaco Jet. This study compares two situations where the NAL is present in the continent’s subtropics: one where it is coupled with an extratropical transient trough to its south and another without this coupling. The coupled case, called the front case, is stronger in two ways: it is warmer and shows lower geopotential at the center of the NAL. It also shows much stronger moisture transport. Both cases show a similar trait in that moisture transport and the zonal component of the geopotential gradient east of the NAL peak in the coolest hours. The geopotential at the center of the no-front case remains roughly constant throughout the event. For the front case, it attains its minimum value in the six hours preceding the northeastward advance of the transient trough. These results suggest that there are different mechanisms acting at the center of the NAL and at its eastern branch, as well as in the front and no-front cases.
Citation: Atmosphere
PubDate: 2023-05-18
DOI: 10.3390/atmos14050883
Issue No: Vol. 14, No. 5 (2023)
- Atmosphere, Vol. 14, Pages 884: Dynamical Analyses of a Supercell Tornado
in Eastern China Based on a Real-Data Simulation
Authors: Shiqi Wang, Jinzhong Min
First page: 884
Abstract: Tornadoes are extremely destructive natural disasters, and East China has become a high-incidence area for tornadoes in China in recent years. On 7 July 2013, an EF2-intensity tornado occurred in Gaoyou County, Jiangsu Province in eastern China, within a supercell storm near a Meiyu frontal system. To investigate the dynamical process of the tornado, a numerical simulation was performed using four one-way nested grids within the Advanced Regional Prediction System (ARPS). Data from a nearby operational S-band Doppler radar are assimilated using a 4D ensemble Kalman filter (4DEnKF) at 5 min intervals. Forecasts are run with a nested 50 m grid, capturing the tornado embedded within the supercell storm with a reasonable agreement with observations. The tornadogenesis processes within the simulation results are analyzed in detail, including the three-dimensional evolution of the tornado vortex. It is found that a cold surge within the rear flank downdraft region plays a key role in instigating tornadogenesis when the leading edge of the cold surge approaches a near-ground convergence center located underneath the main updraft, and the enhancement of the convergence center caused by the descending of the low-level mesocyclone is the direct cause of the rapid increase in tornado vorticity. Backward trajectories are calculated based on model output, and the origins of the parcels feeding the intensifying tornado vortex are identified. It is found that parcels from the mid-level of the rear flank downdraft region follow the cold surge, descending to the ground under the influence of the downdraft in the cold surge, and then entering the convergence center, merging into the core of the tornado and being lifted up. Vertical profiles of the mass and vorticity fluxes into the core of the tornado vortex are examined, and it is found that the near-ground airflow contributes significantly to the growth of the tornado vorticity, with the contribution increasing as it gets closer to the ground.
Citation: Atmosphere
PubDate: 2023-05-18
DOI: 10.3390/atmos14050884
Issue No: Vol. 14, No. 5 (2023)
- Atmosphere, Vol. 14, Pages 885: Thermal Hazards Evaluation Based on Weight
of Evidence Method in the Resource Area of Datong River in Qinghai-Tibetan
Plateau
Authors: Wang, Sheng, Jia, Ren
First page: 885
Abstract: With global warming and increasingly frequent human activities in permafrost regions, it is of great significance to accurately and scientifically evaluate the probability and scope of thermal hazards in permafrost regions. Based on remote sensing image interpretation and field survey, the weight of evidence method (WoEM) was used to comprehensively evaluate the risk of thermal hazards in the source area of the Datong River. There were 10 factors, such as ground ice, mean annual ground temperature, mean annual air temperature, and ground soil type etc., selected in the WoEM. The results showed that the thermal hazard occurrences were closely influenced by ground ice, mean annual ground temperature, ground soil type, etc. The thermal hazards mainly occurred in the unstable permafrost with MAGT of –0.5 to –1.5 °C, accounting for 54.72% of the thermal hazards. The distribution area of thermal hazards in ground ice Level I and II accounts for 66.42%. Thermal hazards mainly occur in the soil types of bog soil and sapropel bog soil, accounting for 41.24% and 29.62% of the total thermal hazards area, respectively. Based on the influence factors and WoEM of thermal hazards occurrence, the probability map of thermal hazards occurrence in the source area was obtained. Additionally, the characteristics of the region with a high probability of thermal hazards occurrence and their causes were also comprehensively analyzed.
Citation: Atmosphere
PubDate: 2023-05-18
DOI: 10.3390/atmos14050885
Issue No: Vol. 14, No. 5 (2023)
- Atmosphere, Vol. 14, Pages 886: System Predictability Assessed by Low
Wavenumber Fourier Components and Analogue Pair Progression of
Geopotential Height
Authors: Liddle, Moosmüller, Lewis
First page: 886
Abstract: Following Lorenz’s work using analogue pairs for establishing 10-to-14-day predictability limits for synoptic weather regimes, predictability limits for the Rex block, the long-wave wintertime ridge over the eastern Pacific Ocean and the western United States, have been estimated. This was accomplished by using mid-latitude geopotential height reanalysis data over a period of 38 years, 1979–2016, and associated 90-day winters (DJF). The metric used to define analogue pairs is the RMS difference assessed for the hemispheric 850, 500, and 200 hPa geopotential height fields. The resultant set of analogue pairs was used to estimate predictability with respect to both a single latitude circle (40° N) that passes through the Rex Block and for a multi-latitude swath (20–80° N). Our methods showed a range of results, by choice of Fourier component wavenumbers 2 through 8. These results indicate system predictability for low wavenumber components to exceed the 10–14-day limit imposed by Lorenz’ results. The results to 21 days, the maximum predictability limit value allowed by our method, do not preclude the possibility of a greater range of system predictability past 21 days. The unique aspect of this work is determination of predictability limits as a function of geopotential wave structure found through Fourier decomposition.
Citation: Atmosphere
PubDate: 2023-05-18
DOI: 10.3390/atmos14050886
Issue No: Vol. 14, No. 5 (2023)
- Atmosphere, Vol. 14, Pages 887: The Air and Viruses We Breathe: Assessing
the Effect the PM2.5 Air Pollutant Has on the Burden of COVID-19
Authors: Sherrie L. Kelly, Andrew J. Shattock, Martina S. Ragettli, Danielle Vienneau, Ana M. Vicedo-Cabrera, Kees de Hoogh
First page: 887
Abstract: Evidence suggests an association between air pollutant exposure and worse outcomes for respiratory viral diseases, like COVID-19. However, does breathing polluted air over many years affect the susceptibility to SARS-CoV-2 infection or severity of COVID-19 disease, and how intense are these effects' As climate change intensifies, air pollutant levels may rise, which might further affect the burden of respiratory viral diseases. We assessed the effect of increasing exposure to PM2.5 (particulate matter ≤ 2.5 microns in diameter) on SARS-CoV-2 susceptibility or COVID-19 severity and projected the impact on infections and hospitalisations over two years. Simulations in a hypothetical, representative population show that if exposure affects severity, then hospital admissions are projected to increase by 5–10% for a one-unit exposure increase. However, if exposure affects susceptibility, then infections would increase with the potential for onward transmission and hospital admissions could increase by over 60%. Implications of this study highlight the importance of considering this potential additional health and health system burden as part of strategic planning to mitigate and respond to changing air pollution levels. It is also important to better understand at which point PM2.5 exposure affects SARS-CoV-2 infection through to COVID-19 disease progression, to enable improved protection and better support of those most vulnerable.
Citation: Atmosphere
PubDate: 2023-05-19
DOI: 10.3390/atmos14050887
Issue No: Vol. 14, No. 5 (2023)
- Atmosphere, Vol. 14, Pages 888: Study of Landfalling Typhoon Potential
Maximum Gale Forecasting in South China
Authors: Su, Li, Ren, Zhu, Liu, Wan, Sun, Jia
First page: 888
Abstract: Based on historical tropical cyclone (TC) tracking data and wind data from observation stations, four comparison experiments were designed that considered TC translation speed similarity and five new ensemble schemes in an improved Dynamical-Statistical-Analog Ensemble Forecast (DSAEF) model for Landfalling Typhoon Gale (LTG), which was tested in terms of forecast capability in South China. The results showed that the improved DSAEF_LTG model with the incorporation of TC translation speed and a new ensemble scheme could improve the forecast threat score (TS) and reduce both the false alarm ratio and the missing ratio in comparison with corresponding values attained before the improvement. The TS of the new ensemble scheme model (DLTG_3) was 0.34 at threshold above Beaufort Scale 7, which was 31% better than that of the unimproved model (DLTG_1). At a threshold above Beaufort Scale 10, the TS of DLTG_3 indicated even greater improvement, reaching 0.25, i.e., 127% higher than that of DLTG_1. The results of the experiments illustrated the marked improvement achievable when using the new ensemble scheme. The reasons for the differences in the DSAEF_LTG model forecasts before and after the introduction of TC translation speed and the new ensemble scheme were analyzed for the cases of Typhoon Haima and Typhoon Hato.
Citation: Atmosphere
PubDate: 2023-05-19
DOI: 10.3390/atmos14050888
Issue No: Vol. 14, No. 5 (2023)
- Atmosphere, Vol. 14, Pages 889: Occurrence Characteristics of VHF
Scintillation and Equatorial Spread F over Kwajalein during Moderate Solar
Activity in 2012
Authors: Chao-Song Huang
First page: 889
Abstract: The occurrence probability of equatorial plasma bubbles and the associated spread F (ESF) irregularities have been derived from ground-based and space-borne measurements. In general, ESF occurrence depends on season and longitude and is high in equinoctial months and low around June solstice. In the West Pacific sector, previous statistical results show that the ESF occurrence probability increases gradually and continuously from March to August. In this study, we use trans-ionospheric VHF data received at Kwajalein Atoll in 2012 to derive the occurrence characteristics of scintillation. It is found that the occurrence probability of strong scintillation had two maxima in June and September and a minimum in July in the evening and midnight sector but only one maximum in June in the post-midnight sector. The monthly variations of scintillation occurrence at Kwajalein are different from almost all previous studies on ESF and scintillation at or near this longitude. To identify the cause for the June peak and the July minimum of scintillation, the ion density and velocity data measured by the Communication/Navigation Outage Forecasting System (C/NOFS) satellite in 2011–2012 are used to derive the ESF occurrence and the post-sunset vertical ion drift near Kwajalein. The ESF occurrence probability and the ion drift measured by the C/NOFS satellite showed two maxima in May/June and August/September and a minimum in July, verifying that the June peak and the July minimum of the VHF scintillation are realistic and caused by the similar variations in the ionospheric ion drift and density.
Citation: Atmosphere
PubDate: 2023-05-19
DOI: 10.3390/atmos14050889
Issue No: Vol. 14, No. 5 (2023)
- Atmosphere, Vol. 14, Pages 890: Investigation of Dynamical Complexity in
Swarm-Derived Geomagnetic Activity Indices Using Information Theory
Authors: Georgios Balasis, Adamantia Zoe Boutsi, Constantinos Papadimitriou, Stelios M. Potirakis, Vasilis Pitsis, Ioannis A. Daglis, Anastasios Anastasiadis, Omiros Giannakis
First page: 890
Abstract: In 2023, the ESA’s Swarm constellation mission celebrates 10 years in orbit, offering one of the best ever surveys of the topside ionosphere. Among its achievements, it has been recently demonstrated that Swarm data can be used to derive space-based geomagnetic activity indices, similar to the standard ground-based geomagnetic indices monitoring magnetic storm and magnetospheric substorm activity. Recently, many novel concepts originating in time series analysis based on information theory have been developed, partly motivated by specific research questions linked to various domains of geosciences, including space physics. Here, we apply information theory approaches (i.e., Hurst exponent and a variety of entropy measures) to analyze the Swarm-derived magnetic indices from 2015, a year that included three out of the four most intense magnetic storm events of the previous solar cycle, including the strongest storm of solar cycle 24. We show the applicability of information theory to study the dynamical complexity of the upper atmosphere, through highlighting the temporal transition from the quiet-time to the storm-time magnetosphere, which may prove significant for space weather studies. Our results suggest that the spaceborne indices have the capacity to capture the same dynamics and behaviors, with regards to their informational content, as traditionally used ground-based ones.
Citation: Atmosphere
PubDate: 2023-05-19
DOI: 10.3390/atmos14050890
Issue No: Vol. 14, No. 5 (2023)
- Atmosphere, Vol. 14, Pages 891: A Two-Stage Hybrid Model for Determining
the Scopes and Priorities of Joint Air Pollution Control
Authors: Pingle Yang, Hongru Yi, Laijun Zhao, Luping Chen
First page: 891
Abstract: Due to the spillover nature of air pollution, the territorial separate governance mode is ineffective in combating pollution, making Joint Prevention and Control of Air Pollution (JPCAP) among multiple regions the only viable option. However, determining the appropriate scopes and priorities for JPCAP is known to be a challenging and significant issue. To address this, we propose a new two-stage hybrid model. In the first stage, making use of long-term, wide area monitoring data provided by the air pollution monitoring network, we propose a new method for subdividing large regions into sub-regions by using data mining techniques. In the second stage, we propose a comprehensive decision-making framework to evaluate the priorities of JPCAP sub-regions from three different perspectives, namely, the impact of a sub-region on the pollution level of the entire target region, as well as the urgency and elasticity of sub-regional air pollution control. A case study is conducted on 27 cities of the Yangtze River Delta region of China. The case study demonstrates the validity and practicality of the proposed two-stage hybrid model. This work provides a viable tool for the effective implementation of air pollution control in China and other regions of the world.
Citation: Atmosphere
PubDate: 2023-05-19
DOI: 10.3390/atmos14050891
Issue No: Vol. 14, No. 5 (2023)
- Atmosphere, Vol. 14, Pages 892: Analysis of Data on Air Pollutants in the
City by Machine-Intelligent Methods Considering Climatic and Geographical
Features
Authors: Nurlan Temirbekov, Syrym Kasenov, Galym Berkinbayev, Almas Temirbekov, Dinara Tamabay, Marzhan Temirbekova
First page: 892
Abstract: In the world, air pollution ranks among the primary sources of risk to human health and the environment. To assess the risk of impact of atmospheric pollution, a comprehensive research cycle was designed to develop a unified ecosystem for monitoring air pollution in industrial cities in Kazakhstan. Research involves analyzing data for the winter period from 20 automated monitoring stations (AMS) located in Almaty and conducting chemical-analytical studies of snowmelt water samples from 22 points to identify such pollutants as fine particulate matters, petroleum products, and heavy metals. Research includes a bio-experiment involving the cultivation of watercress on samples of melt water collected from snow cover to examine the effects of pollution on plants. In the framework of this research, we determined API based on data obtained from AMS. In order to determine the influence of atmospheric pollution on the environment, a multiple regression model was developed using machine learning algorithms to reveal the relationship between the bio-experiment data and data on pollutants of chemical-analytical research. The results revealed a wide spread of pollutants in the snow cover of the urban environment, a correlation between pollutants in the snow cover and the airspace of the city, and their negative impact on flora.
Citation: Atmosphere
PubDate: 2023-05-20
DOI: 10.3390/atmos14050892
Issue No: Vol. 14, No. 5 (2023)
- Atmosphere, Vol. 14, Pages 893: Comparison of Trace Element Deposition in
Cupressus macrocarpa Leaves and Soils from a High-Pollution Area in the
Puchuncaví Valley (Chile) Using a Biomonitoring Method
Authors: Tamara Gorena, Franco Sandoval, Ximena Fadic, Francisco Cereceda-Balic
First page: 893
Abstract: Located in the Puchuncaví Valley (PV) in central Chile is one of the most important and oldest industrial complexes (ICs) in the country. The PV is affected by anthropogenic emissions from the IC where the most important industry is a copper smelter and refinery. In this context, this study assessed the profile, concentration, and enrichment factors of the trace elements, both in the soil and in Cupressus macrocarpa leaves from this high-pollution-load area. The soil and leaf samples were taken from five selected sites, located between 0.8 and 15 km away from the IC. A total of 24 elements were analyzed by ICP-MS and examined by enrichment factor (EF), and PCA source analysis. Leaf concentrations of Ba, Ca, Cd, Cu, K, and Sr showed statistically significant differences between sampling sites (p-value < 0.05). In soil, element concentrations of Al, As, Ba, Cr, Cu, K, Li Mg, Mn, Na, Ni, Pb, and Ti showed statistically significant differences between sampling sites (p-value < 0.05). The source analysis of EFs in the samples of both soil and leaves detected three and four factors, respectively, related mainly to the industrial complex’s copper smelter and refinery, coal-fired power plants, and geogenic sources. According to the PCA, the leaf EFs of anthropogenic elements from copper smelting showed that La Greda (LG, site closest to the IC) was significantly enriched in the elements Cu, Zn, As, Mo, and Pb, while the EF in the soil from LG showed high enrichment in Cu and significant enrichment in Pb.
Citation: Atmosphere
PubDate: 2023-05-20
DOI: 10.3390/atmos14050893
Issue No: Vol. 14, No. 5 (2023)
- Atmosphere, Vol. 14, Pages 894: The Vertical Distributions of Aerosol
Optical Characteristics Based on Lidar in Nanyang City from 2021 to 2022
Authors: Miao Zhang, Si Guo, Yunuo Wang, Shiyong Chen, Jinhan Chen, Mingchun Chen, Muhammad Bilal
First page: 894
Abstract: To investigate the vertical distribution of aerosol optical characteristics in Nanyang City, a ground-based dual-wavelength (532 nm and 355 nm) lidar system was developed for aerosol observation at the Nanyang Normal University Station (NYNU) from November 2021 to December 2022. Spatio-temporal dynamics information on vertical distributions of aerosol optical properties during polluted and non-polluted days was obtained. Aerosols were characterized by low altitudes (up to 2 km), thinner layers, and high-altitude (up to 4 km) thick layers during non-polluted and polluted days, with extinction coefficient values of ~0.03 km−1 and ~0.2 km−1, respectively. The mean values of the extinction coefficient at different altitudes (0~5 km) were all about ten-times higher on polluted days (0.04~0.19 km−1) than on non-polluted days (0.004~0.02 km−1). These results indicate that aerosol loadings and variations at different altitudes (0~5 km) were much higher and more prominent on polluted days than non-polluted days. The results show ten-times larger aerosol optical depth (AOD) values (0.4~0.6) on polluted days than on non-polluted days (0.05~0.08). At the same time, AOD values on both polluted and non-polluted days slightly decreased from 19:00 to 05:00, possibly due to dry depositions at nighttime. For the first time, this study established a ground-based lidar remote sensing system to investigate the vertical distribution of atmospheric aerosol optical characteristics in Henan Province. The experimental results can provide scientific dataset support for the local government to prevent and control air pollution.
Citation: Atmosphere
PubDate: 2023-05-20
DOI: 10.3390/atmos14050894
Issue No: Vol. 14, No. 5 (2023)
- Atmosphere, Vol. 14, Pages 895: Detection of Migrating and Non-Migrating
Atmospheric Tides Derived from ERA5 Temperature Meteorological Analyses
Authors: Philippe Keckhut, Thomas Lefebvre, Alain Hauchecorne, Mustapha Meftah, Sergey Khaykin
First page: 895
Abstract: To better extract the tides represented in the European meteorological analysis ERA5, an analysis of the histograms of the diurnal and semi-diurnal modes as a function of longitudes was performed. This analysis revealed that modes with different characteristics appeared regionally along a single longitude. Retrieved migrating tides were compared with a tidal model showing global agreement below 60 km and twice the amplitude in meteorological analyses at mid-latitude. Non-migrating tidal modes have been identified along the tropical band. They logically appear above the convective zones, probably due to water vapor excess. Their characteristics are different from migrating components. This preliminary study has shown that it is necessary to develop additional observations allowing for more frequent sampling to retrieve migrating and non-migrating tides that can only be achieved with satellite constellations from space.
Citation: Atmosphere
PubDate: 2023-05-20
DOI: 10.3390/atmos14050895
Issue No: Vol. 14, No. 5 (2023)
- Atmosphere, Vol. 14, Pages 896: Brightness Temperature Characteristics of
Short-Duration Heavy Rainfall in the Chengdu–Chongqing Railway
Region in China
Authors: Xinchao Liu, Yongren Chen, Jie Guo, Wenwen Song, Jia Dan
First page: 896
Abstract: In this study, we analyzed the brightness temperature characteristics of short-duration heavy rainfall (SDHR) along the Chengdu–Chongqing Railway (CCR), an important corridor of economic and transportation activity in southwest China. Our findings could prove useful in the monitoring and advance warning of SDHR events: (1) SDHR predominantly occurred from July to August, with a peak frequency in July in the CCR area. In terms of diurnal variation, SDHR was mainly observed at night, particularly between 22:00–05:00 and 06:00–09:00 (local time), with a peak at 01:00; (2) The relationship between SDHR and equivalent blackbody temperature (TBB) further showed that the occurrence of SDHR was accompanied by TBB decreasing to its minimum value, after which it increased, and SDHR ceased. In cases where TBB approached its minimum value after 1 h but continued to decrease slightly, SDHR continued. When SDHR occurred, the majority of the TBB values were recorded in the range 190–230 K; within this range, values between 190 and 200 K were most frequently recorded. In general, lower TBB values are associated with more intense SDHR. Based on this finding, we used linear regression to establish an estimating equation for SDHR.
Citation: Atmosphere
PubDate: 2023-05-20
DOI: 10.3390/atmos14050896
Issue No: Vol. 14, No. 5 (2023)
- Atmosphere, Vol. 14, Pages 897: Exploring the Relationship between
Hydroclimate and Lake Area in Source Area of the Yellow River:
Implications for the Paleoclimate Studies
Authors: Shuying Bai, Jixi Gao, Yang Pu, Da Zhi, Jiaojiao Yao
First page: 897
Abstract: The large tectonic lake is one of the most important water bodies in the source area of the Yellow River (SAYR), northeastern Qinghai-Tibet Plateau (QTP). It plays a key role in decelerating climatic change and regulating regional climate patterns. In this study, we used Landsat images (MSS, TM, ETM+ and OLI) of Lake Gyaring and Lake Ngoring (the Two Sisters Lakes), which are the two largest tectonic lakes in the SAYR, to determine annual lake area fluctuations from 1986 to 2020. The results show that lake area increases were generally consistent with a warming trend in the SAYR. The temperature signals were separated from the lake area changes by using a detrending analysis and found that the processed data are closely correlated with variations of precipitation and streamflow in the SAYR, and the previously reported paleoclimate records, which include the δ18O record from stalagmite, A/C (Artemisia/Chenopodiaceae) ratio from lake sediment and scPDSI (self-calibrating Palmer Drought Severity Index) from the tree ring on the northeastern margin of the QTP. The phase of relatively large lake areas typically coincides with a negative excursion in δ18O, a high A/C ratio, and elevated scPDSI values, while the opposite is true for smaller lake areas. It is suggested that the total area of the Two Sisters Lakes is closely associated with hydroclimatic conditions in the SAYR. Furthermore, an association of high TSI anomalies with the water area expansion of the Two Sisters Lakes is also observed, implying that solar activity is the key driving factor for the hydrologic variability in the SAYR on decadal timescales. The findings of our study highlight the validity of previous paleoclimate archives in the northeastern QTP and demonstrate the potential of using remote sensing techniques to investigate paleoclimate.
Citation: Atmosphere
PubDate: 2023-05-21
DOI: 10.3390/atmos14050897
Issue No: Vol. 14, No. 5 (2023)
- Atmosphere, Vol. 14, Pages 898: The Impact of COVID-19 Lockdown on Ambient
Air Quality in Shanghai, 2022
Authors: Qi Zhang, Qian Zhang, Hui Liu, Mingyue Lu
First page: 898
Abstract: The COVID-19 lockdown contributes to the improvement of air quality. Most previous studies have attributed this to the reduction of human activity while ignoring the meteorological changes, this may lead to an overestimation or underestimation of the impact of COVID-19 lockdown measures on air pollution levels. To investigate this issue, we propose an XGBoost-based model to predict the concentrations of PM2.5 and PM10 during the COVID-19 lockdown period in 2022, Shanghai, and thus explore the limits of anthropogenic emission on air pollution levels by comprehensively employing the meteorological factors and the concentrations of other air pollutants. Results demonstrate that actual observations of PM2.5 and PM10 during the COVID-19 lockdown period were reduced by 60.81% and 43.12% compared with the predicted values (regarded as the period without the lockdown measures). In addition, by comparing with the time series prediction results without considering meteorological factors, the actual observations of PM2.5 and PM10 during the lockdown period were reduced by 50.20% and 19.06%, respectively, against the predicted values during the non-lockdown period. The analysis results indicate that ignoring meteorological factors will underestimate the positive impact of COVID-19 lockdown measures on air quality.
Citation: Atmosphere
PubDate: 2023-05-21
DOI: 10.3390/atmos14050898
Issue No: Vol. 14, No. 5 (2023)
- Atmosphere, Vol. 14, Pages 899: Time–Frequency Characteristics and
SARIMA Forecasting of Atmospheric Water Vapor in East Asia
Authors: Chaoli Tang, Ziyue Tong, Yuanyuan Wei, Xin Wu, Xiaomin Tian, Jie Yang
First page: 899
Abstract: Given the increasing impact of extreme rainfall and flooding on human life, studying and predicting changes in atmospheric water vapor (AWV) becomes particularly important. This paper analyzes the moderate-resolution imaging spectroradiometer (MODIS) data of the East Asian region from January 2003 to February 2023. The AWV data are examined in the time and frequency domain using methods such as empirical orthogonal function (EOF), Mann–Kendall (MK) analysis, and others. Additionally, four prediction models are applied to forecast the monthly average AWV data for the next year. The accuracy of these models is evaluated using metrics such as mean square error (MSE), mean absolute error (MAE), root mean square error (RMSE), and coefficient of determination (R2). The findings reveal several key insights: (1) The East Asian region exhibits highly variable seasonal variability in AWV, with identified mutation points after the MK test. (2) Spatial analysis shows high AWV data in the southern coastal areas of China, Thailand, Myanmar, Nansha Islands, and other regions during winter, while the Qinghai-Tibet Plateau region experiences low AWV during summer. (3) The first mode obtained through EOF decomposition contributes over 60% of the variance. Analysis of this mode reveals an increasing trend in AWV data for regions such as the Indian peninsula, Mongolia, and central and northeastern China over the past nine years. Conversely, the Bay of Bengal, Spratly Islands, eastern coast, and certain areas display a decreasing trend. (4) Employing the ensemble empirical mode decomposition (EEMD), the study identifies AWV data as a non-stationary series with an overall decreasing trend from 2003 to 2022. The filtered AWV series undergoes fast Fourier transform (FFT), uncovering periodicities of 2.6 years, 5 years, and 19 years. (5) Among the four forecasting models compared, the seasonal autoregressive integrated moving average model (SARIMA) demonstrates superior performance with the smallest MSE of 0.00782, MAE of 0.06977, RMSE of 0.08843, and the largest R2 value of 0.98454. These results clearly indicate that the SARIMA model provides the best fit. Therefore, the SARIMA forecasting model can be effectively utilized for forecasting AWV data, offering valuable insights for studying weather variability.
Citation: Atmosphere
PubDate: 2023-05-21
DOI: 10.3390/atmos14050899
Issue No: Vol. 14, No. 5 (2023)
- Atmosphere, Vol. 14, Pages 900: Nexus between Social Vulnerability and
Resilience to Agricultural Drought amongst South African Smallholder
Livestock Households
Authors: Yonas T. Bahta, Willem A. Lombard
First page: 900
Abstract: Livestock farmers in Sub-Saharan Africa rely on rain-fed agriculture, which exposes them to the risks of agricultural drought. Agricultural drought has become a significant threat to the extreme mortality of livestock, thus negatively impacting social vulnerability and household resilience to agricultural drought and extreme events. Researchers rarely empirically assess the connection between vulnerability and resilience, which are highly related concepts. By measuring and connecting vulnerability and resilience concepts closely related to disasters such as agricultural drought, this article makes a contribution to the body of disaster literature. The study aimed to empirically examine the relationship between smallholder livestock farming households’ social vulnerability and their resilience to agricultural drought. A survey of 217 smallholder livestock farmers was conducted. The Social Vulnerability Index (SVI), the Agricultural Drought Resilience Index (ADRI), and Pearson’s correlation coefficient were used for data analysis. A correlation was identified between resilience to agricultural drought and social vulnerability, indicating that smallholder livestock farmers are more susceptible to harm and lack the means to rebound effectively. Unsurprisingly, the majority of resource-poor smallholder livestock farmers (79%) lack safety nets during agricultural droughts. They are less resilient and more vulnerable households, leading them to social vulnerability. This study provides input/guidance to identify farming households with high social vulnerability and less resilience to threats and their capabilities of recouping and adopting after experiencing an agricultural drought. Additionally, looking at household resilience and social vulnerability to agricultural droughts could provide a way to pinpoint at-risk areas, assisting emergency planners in directing resources and intervention programs to those areas where assistance is most likely to be needed during disasters such as agricultural droughts. This implies that thorough policy intervention programs need to be tailored toward reducing damage or finding the path to recovery.
Citation: Atmosphere
PubDate: 2023-05-21
DOI: 10.3390/atmos14050900
Issue No: Vol. 14, No. 5 (2023)
- Atmosphere, Vol. 14, Pages 901: Remote Polar Boundary Layer Wind Profiling
Using an All-Fiber Pulsed Coherent Doppler Lidar at Zhongshan Station,
Antarctica
Authors: Hui Li, Zhangjun Wang, Quanfeng Zhuang, Rui Wang, Wentao Huang, Chao Chen, Xianxin Li, Xiufen Wang, Boyang Xue, Yang Yu, Xin Pan
First page: 901
Abstract: A compact all-fiber pulsed coherent Doppler lidar (PCDL) for boundary layer wind measurement was developed by the Institute of Oceanographic Instrumentation, Qilu University of Technology (Shandong Academy of Sciences). It has been deployed at Zhongshan Station (69.4° S, 76.4° E) during the 2020 austral summer season by the 36th Chinese National Antarctic Research Expedition (CHINARE) and started routine observation in January 2020. This system, based on the 1550 nm all-fiber components, employs a 100 mm telescope with a long focal length of 632.6 mm to emit and collect laser pulses. It provides the ability to measure vertically resolved wind fields with a spatial resolution of 30 m and a temporal resolution of 1 min; the maximum detection range is up to 1.5 km in Antarctica. Wind speed and direction inversion methods were introduced subsequently. Preliminary measurement results of wind profiles indicate that this Doppler lidar can be operated successfully in Antarctica. The synchronous observations between the lidar, anemometer, and radiosondes at Zhongshan station are presented and have good consistency with each other. The comparison results between the lidar and anemometer indicate a root mean square deviation (RMSD) of 0.98 m s−1 and 10.55° for wind speed and direction, respectively. The lidar continuous observations of wind profiles provide an opportunity to study the spatiotemporal variation of Antarctic wind with high resolutions, which is useful for further understanding of the atmosphere in Antarctic regions.
Citation: Atmosphere
PubDate: 2023-05-22
DOI: 10.3390/atmos14050901
Issue No: Vol. 14, No. 5 (2023)
- Atmosphere, Vol. 14, Pages 902: Predicting the Impact of Change in Air
Quality Patterns Due to COVID-19 Lockdown Policies in Multiple Urban
Cities of Henan: A Deep Learning Approach
Authors: Mughair Aslam Bhatti, Zhiyao Song, Uzair Aslam Bhatti, Naushad Ahmad
First page: 902
Abstract: Several countries implemented prevention and control measures in response to the 2019 new coronavirus virus (COVID-19) pandemic. To study the impact of the lockdown due to COVID-19 on multiple cities, this study utilized data from 18 cities of Henan to understand the air quality pattern change during COVID-19 from 2019 to 2021. It examined the temporal and spatial distribution impact. This study firstly utilized a deep learning bi-directional long-term short-term (Bi-LSTM) model to predict air quality patterns during 3 periods, i.e., COVID-A (before COVID-19, i.e., 2019), COVID-B (during COVID-19, i.e., 2020), COVID-C (after COVID-19 cases, i.e., 2021) and obtained the R2 value of more than 72% average in each year and decreased MAE value, which was better than other studies’ deep learning methods. This study secondly focused on the change of pollutants and observed an increase in Air Quality Index by 10%, a decrease in PM2.5 by 14%, PM10 by 18%, NO2 by 14%, and SO2 by 16% during the COVID-B period. This study found an increase in O3 by 31% during the COVID-C period and observed a significant decrease in pollutants during the COVID-C period (PM10 by 42%, PM2.5 by 97%, NO2 by 89%, SO2 by 36%, CO by 58%, O3 by 31%). Lastly, the impact of lockdown policies was studied during the COVID-B period and the results showed that Henan achieved the Grade I standards of air quality standards after lockdown was implemented. Although there were many severe effects of the COVID-19 pandemic on human health and the global economy, lockdowns likely resulted in significant short-term health advantages owing to reduced air pollution and significantly improved ambient air quality. Following COVID-19, the government must take action to address the environmental problems that contributed to the deteriorating air quality.
Citation: Atmosphere
PubDate: 2023-05-22
DOI: 10.3390/atmos14050902
Issue No: Vol. 14, No. 5 (2023)
- Atmosphere, Vol. 14, Pages 903: PM2.5 Concentration Prediction in Six
Major Chinese Urban Agglomerations: A Comparative Study of Various Machine
Learning Methods Based on Meteorological Data
Authors: Min Duan, Yufan Sun, Binzhe Zhang, Chi Chen, Tao Tan, Yihua Zhu
First page: 903
Abstract: The escalating issue of air pollution in China’s rapidly developing urban areas has prompted increased attention to the role of meteorological conditions in PM2.5 pollution. This study examines the spatiotemporal distribution of PM2.5 concentrations and their relationship with meteorological factors in six major Chinese urban agglomerations from 2017 to 2020, using daily average data. Statistical and spatial analysis techniques are employed, alongside the construction of eight machine learning models for prediction purposes. The study also compares the feature importance of various meteorological factors impacting PM2.5 concentrations. Results reveal significant regional differences in both average PM2.5 levels and meteorological influences. The Multilayer Perceptron (MLP) model demonstrates the highest prediction accuracy for PM2.5 concentrations. According to the MLP model’s feature importance identification, temperature is the most significant factor affecting PM2.5 concentrations across all urban agglomerations, while wind speed and precipitation have the least impact. Contributions from air pressure and dew point temperature, however, vary among different urban agglomerations. This research considers the impact of urban agglomerations and meteorological conditions on PM2.5 and also offers valuable artificial intelligence-based insights into the key meteorological factors influencing PM2.5 concentrations in diverse regions, thereby informing the development of effective air pollution control policies.
Citation: Atmosphere
PubDate: 2023-05-22
DOI: 10.3390/atmos14050903
Issue No: Vol. 14, No. 5 (2023)
- Atmosphere, Vol. 14, Pages 904: Student-Led Research in Atmospheric
Science
Authors: Ari D. Preston, David E. Reed
First page: 904
Abstract: Engaging students in research is critical to their development as atmospheric scientists [...]
Citation: Atmosphere
PubDate: 2023-05-22
DOI: 10.3390/atmos14050904
Issue No: Vol. 14, No. 5 (2023)
- Atmosphere, Vol. 14, Pages 905: Influence of Dynamic and Thermal Effects
of Asian Topography on Tropical Cyclone Activity as Simulated in a Global
Climate Model
Authors: Jinxiao Li
First page: 905
Abstract: Asian topography plays a significant role in regional and global weather and climate change. Based on the dataset of climate system model named CAS FGOALS-f3 participated in Global monsoons Model Inter-comparison (GMMIP), the MIP endorsement of Coupled Model Intercomparison Project Phase 6 (CMIP6), the role of Asian topography to the formation and movement of tropical cyclones (TCs) are discussed in this study. This study provides the first comparative analysis of the dynamic and thermal effects of Asian topography on the regional and global activity of TCs. The results indicate that the Asian topography promotes the generation and development of TCs, especially in the Northwest Pacific (WNP). The contribution of the Asian topography to the number of TCs reached about 50% in WNP. It is worth noting that there are still positive biases of TC track density in the experiment named “AMIP-NS”, which means the thermal effect of Asian topography is also essential for TC formation and development in WNP, which has not received much attention before. Besides, the possible reasons for the modulation of TC activity are given from two aspects: (1) The existence of Asian topography has changed the large-scale factors related to TC activities such as warm core, sea-level pressure, genesis potential index (GPI), which are beneficial to the generation and movement of TC. (2) Asian topography promotes the spread of Madden–Julian oscillation (MJO), which is also beneficial to the generation and movement of TC. It is worthwhile to investigate further the mechanisms by which Asian topography affects the activity of TCs.
Citation: Atmosphere
PubDate: 2023-05-22
DOI: 10.3390/atmos14050905
Issue No: Vol. 14, No. 5 (2023)
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