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Volume 11
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Atmosphere, Volume 11, Issue 1 (January 2020) – 121 articles

Cover Story (view full-size image): Concerning the study of the atmospheric dispersion, it can be recalled that much research has been devoted to modeling the mean concentration. Nevertheless, other statistical properties than the mean have practical importance in a large number of applications as second and higher order moments of concentration. For example, concentration variance or covariance may be required in the study of toxic gas effects on humans, assessment of nuisance due to malodorous materials, flammability of substances, and interaction between turbulence and chemistry. A review of the Lagrangian stochastic models developed in recent decades for the simulation of concentration–fluctuation dispersion is presented. Then, Lagrangian approaches for evaluating of odor annoyance are described and discussed. View this paper.
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17 pages, 2591 KiB  
Article
Influence of Weather on the Behaviour of Tourists in a Beach Destination
by Diego R.-Toubes, Noelia Araújo-Vila and José Antonio Fraiz-Brea
Atmosphere 2020, 11(1), 121; https://doi.org/10.3390/atmos11010121 - 20 Jan 2020
Cited by 30 | Viewed by 12501
Abstract
In sun-and-beach destinations, weather has a decisive influence on the variability of the daily flow of tourists. Uncertainty in demand flows directly affects businesses and employment. This work aims to improve understanding of the behaviour of tourists in response to changes in weather [...] Read more.
In sun-and-beach destinations, weather has a decisive influence on the variability of the daily flow of tourists. Uncertainty in demand flows directly affects businesses and employment. This work aims to improve understanding of the behaviour of tourists in response to changes in weather conditions. The analysis is carried out in the Rías Baixas, a sun-and-beach destination in north-west Spain. The paper analyses the relationship of weather conditions with daily flows during the high season at the main tourist beaches in the area, also considering two beach typologies. The density of beach use is measured three times a day through the analysis of webcam images in combination with real-time weather, and an online survey is conducted among tourists who have visited these beaches. The results show that the hours of sunshine are the most influential weather factor. Weather forecast greatly or totally influenced the decision to go to the beach for almost 70% of respondents and about 80% of the respondents checked on the weather before visiting a beach. Full article
(This article belongs to the Special Issue Tourism Climatology: Past, Present and Future)
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12 pages, 6493 KiB  
Article
Sensitivity Analysis of Surface Energy Budget to Albedo Parameters in Seoul Metropolitan Area Using the Unified Model
by Jieun Wie, Seon-Ok Hong, Jae-Young Byon, Jong-Chul Ha and Byung-Kwon Moon
Atmosphere 2020, 11(1), 120; https://doi.org/10.3390/atmos11010120 - 20 Jan 2020
Cited by 8 | Viewed by 3943
Abstract
The large population growth has significantly altered the thermal characteristics of the atmosphere, including decreased albedo and increased heat capacity; thus, urban areas experience unique climatic phenomena. We conducted sensitivity experiments using Unified Model Local Data Assimilation and Prediction-Met-Office-Reading Urban Surface Exchange Scheme [...] Read more.
The large population growth has significantly altered the thermal characteristics of the atmosphere, including decreased albedo and increased heat capacity; thus, urban areas experience unique climatic phenomena. We conducted sensitivity experiments using Unified Model Local Data Assimilation and Prediction-Met-Office-Reading Urban Surface Exchange Scheme (LDAPS-MORUSES) to investigate the response of surface energy budget to albedo changes in the Seoul Metropolitan Area. We compared 1.5-m temperature at 56 automatic weather station (AWS) sites and showed underestimations of approximately 0.5–2 K, but the diurnal cycle was well simulated. We changed the wall and road albedo parameters by ±50% from the default values for sensitivity experiments. With increasing albedo, 1.5-m temperature decreased by approximately 0.06 °C and 0.01 °C in urban and suburban areas, respectively. These changes are responses to decreased net radiation and sensible heat during daytime, whereas sensible heat mainly contributes to the surface cooling during nighttime. Furthermore, the decrease in albedo leads to altered vertical structure of potential temperature and atmospheric circulations at altitudes of 300–1000 m. Results show that albedo modification can affect not only surface temperature but also the entire urban boundary layer. Full article
(This article belongs to the Special Issue Urban Meteorology)
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16 pages, 3730 KiB  
Article
Integrated Correction Algorithm for X Band Dual-Polarization Radar Reflectivity Based on CINRAD/SA Radar
by Chao Wang, Chong Wu, Liping Liu, Xi Liu and Chao Chen
Atmosphere 2020, 11(1), 119; https://doi.org/10.3390/atmos11010119 - 20 Jan 2020
Cited by 6 | Viewed by 3567
Abstract
The values of ratio a of the linear relationship between specific attenuation and specific differential phase vary significantly in convective storms as a result of resonance scattering. The best-linear-fit ratio a at X band is determined using the modified attenuation correction algorithm based [...] Read more.
The values of ratio a of the linear relationship between specific attenuation and specific differential phase vary significantly in convective storms as a result of resonance scattering. The best-linear-fit ratio a at X band is determined using the modified attenuation correction algorithm based on differential phase and attenuation, as well as the premise that reflectivity is unattenuated in S band radar detection. Meanwhile, the systemic reflectivity bias between the X band radar and S band radar and water layer attenuation (ZW) on the wet antenna cover of the X band radar are also considered. The good performance of the modified correction algorithm is demonstrated in a moderate rainfall event. The data were collected by four X band dual-polarization (X-POL) radar sites, namely, BJXCP, BJXFS, BJXSY, and BJXTZ, and a China’s New Generation Weather Radar (CINRAD/SA radar) site, BJSDX, in Beijing on 20 July 2016. Ratio a is calculated for each volume scan of the X band radar, with a mean value of 0.26 dB deg−1 varying from 0.20 to 0.31 dB deg−1. The average values of systemic reflectivity bias between the X band radar (at BJXCP, BJXFS, BJXSY, and BJXTZ) and S band radar (at BJSDX) are 0, −3, 2, and 0 dB, respectively. The experimentally determined ZW is in substantial agreement with the theoretically calculated ones, and their values are an order of magnitude smaller than rain attenuation. The comparison of the modified attenuation correction algorithm and the empirical-fixed-ratio correction algorithm is further evaluated at the X-POL radar. It is shown that the modified attenuation correction algorithm in the present paper provides higher correction accuracy for rain attenuation than the empirical-fixed-ratio correction algorithm. Full article
(This article belongs to the Section Atmospheric Techniques, Instruments, and Modeling)
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14 pages, 1984 KiB  
Article
Continuous Detection of Diurnal Sodium Fluorescent Lidar over Beijing in China
by Lifang Du, Jihong Wang, Yong Yang, Yuchang Xun, Faquan Li, Fuju Wu, Shunsheng Gong, Haoran Zheng, Xuewu Cheng, Guotao Yang and Zhenghua Lu
Atmosphere 2020, 11(1), 118; https://doi.org/10.3390/atmos11010118 - 20 Jan 2020
Cited by 1 | Viewed by 3586
Abstract
Based on application of the atomic filter technology in a signal detection system of lidar, the diurnal observation of sodium lidar were obtained using the system at the National Space Science Center of the Chinese Academy of Sciences at Beijing Yanqing station (40.5° [...] Read more.
Based on application of the atomic filter technology in a signal detection system of lidar, the diurnal observation of sodium lidar were obtained using the system at the National Space Science Center of the Chinese Academy of Sciences at Beijing Yanqing station (40.5° N, 116° E) in April 2014. During the lidar observation period, among the 103 cases of continuous daytime observations, the longest time was 181 h. In the case of a continuous observation period of 5 days (13–18 October 2014), the signal-to-noise ratio reached to 19:1 at 12:00–13:00 Local Time of the daytime, when the spatial and time resolutions were respectively set to 96 m of 167 s. The improvements resulted in the highest detection level of any existing diurnal lidars in China. Some interesting phenomena such as the sporadic sodium layer have also been observed during the daytime. The daytime capability extended the observing time range of the earlier systems that were limited to only nighttime observations. This innovation provides a useful method for the studies of diurnal tides, photochemistry, gravity waves, and correlative modeling studies. Full article
(This article belongs to the Special Issue Lidar Remote Sensing Techniques for the Upper Troposphere and the Middle Atmosphere)
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14 pages, 6771 KiB  
Article
The Significance of Wind Turbines Layout Optimization on the Predicted Farm Energy Yield
by Mohammad Al-Addous, Mustafa Jaradat, Aiman Albatayneh, Johannes Wellmann and Sahil Al Hmidan
Atmosphere 2020, 11(1), 117; https://doi.org/10.3390/atmos11010117 - 20 Jan 2020
Cited by 24 | Viewed by 6434
Abstract
Securing energy supply and diversifying the energy sources is one of the main goals of energy strategy for most countries. Due to climate change, wind energy is becoming increasingly important as a method of CO2-free energy generation. In this paper, a [...] Read more.
Securing energy supply and diversifying the energy sources is one of the main goals of energy strategy for most countries. Due to climate change, wind energy is becoming increasingly important as a method of CO2-free energy generation. In this paper, a wind farm with five turbines located in Jerash, a city in northern Jordan, has been designed and analyzed. Optimization of wind farms is an important factor in the design stage to minimize the cost of wind energy to become more competitive and economically attractive. The analyses have been carried out using the WindFarm software to examine the significance of wind turbines’ layouts (M, straight and arch shapes) and spacing on the final energy yield. In this research, arranging the turbines facing the main wind direction with five times rotor diameter distance between each turbine has been simulated, and has resulted in 22.75, 22.87 and 21.997 GWh/year for the M shape, Straight line and Arch shape, respectively. Whereas, reducing the distance between turbines to 2.5 times of the rotor diameter (D) resulted in a reduction of the wind farm energy yield to 22.68, 21.498 and 21.5463 GWh/year for the M shape, Straight line and Arch shape, respectively. The energetic efficiency gain for the optimized wind turbines compared to the modeled layouts regarding the distances between the wind turbines. The energetic efficiency gain has been in the range between 8.9% for 5D (rotor diameter) straight layout to 15.9% for 2.5D straight layout. Full article
(This article belongs to the Special Issue Climate Modeling for Renewable Energy Resource Assessment)
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25 pages, 6396 KiB  
Article
Model of Daytime Oxygen Emissions in the Mesopause Region and Above: A Review and New Results
by Valentine Yankovsky and Ekaterina Vorobeva
Atmosphere 2020, 11(1), 116; https://doi.org/10.3390/atmos11010116 - 19 Jan 2020
Cited by 11 | Viewed by 5441
Abstract
Atmospheric emissions of atomic and molecular oxygen have been observed since the middle of 19th century. In the last decades, it has been shown that emissions of excited oxygen atom O(1D) and molecular oxygen in electronically–vibrationally excited states O2(b [...] Read more.
Atmospheric emissions of atomic and molecular oxygen have been observed since the middle of 19th century. In the last decades, it has been shown that emissions of excited oxygen atom O(1D) and molecular oxygen in electronically–vibrationally excited states O2(b1Σ+g, v) and O2(a1Δg, v) are related by a unified photochemical mechanism in the mesosphere and lower thermosphere (MLT). The current paper consists of two parts: a review of studies related to the development of the model of ozone and molecular oxygen photodissociation in the daytime MLT and new results. In particular, the paper includes a detailed description of formation mechanism for excited oxygen components in the daytime MLT and presents comparison of widely used photochemical models. The paper also demonstrates new results such as new suggestions about possible products for collisional reactions of electronically–vibrationally excited oxygen molecules with atomic oxygen and new estimations of O2(b1Σ+g, v = 0–10) radiative lifetimes which are necessary for solving inverse problems in the lower thermosphere. Moreover, special attention is given to the “Barth’s mechanism” in order to demonstrate that for different sets of fitting coefficients its contribution to O2(b1Σ+g, v) and O2(a1Δg, v) population is neglectable in daytime conditions. In addition to the review and new results, possible applications of the daytime oxygen emissions are presented, e.g., the altitude profiles O(3P), O3 and CO2 can be retrieved by solving inverse photochemical problems when emissions from electronically vibrationally excited states of O2 molecule are used as proxies. Full article
(This article belongs to the Special Issue Atmospheric Airglow—Recent Advances in Observations, Experimentations, and Modeling)
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25 pages, 480 KiB  
Editorial
Acknowledgement to Reviewers of Atmosphere in 2019
by Atmosphere Editorial Office
Atmosphere 2020, 11(1), 115; https://doi.org/10.3390/atmos11010115 - 18 Jan 2020
Viewed by 4174
Abstract
The editorial team greatly appreciates the reviewers who have dedicated their considerable time and expertise to the journal’s rigorous editorial process over the past 12 months, regardless of whether the papers are finally published or not [...] Full article
14 pages, 4818 KiB  
Article
Analysis of Raindrop Shapes and Scattering Calculations: The Outer Rain Bands of Tropical Depression Nate
by Merhala Thurai, Sophie Steger, Franz Teschl and Michael Schönhuber
Atmosphere 2020, 11(1), 114; https://doi.org/10.3390/atmos11010114 - 18 Jan 2020
Cited by 8 | Viewed by 3980
Abstract
Tropical storm Nate, which was a powerful hurricane prior to landfall along the US Gulf coast, traversed north and weakened considerably to a tropical depression as it moved near an instrumented site in Hunstville, AL. The outer rain bands lasted 18 h (03:00 [...] Read more.
Tropical storm Nate, which was a powerful hurricane prior to landfall along the US Gulf coast, traversed north and weakened considerably to a tropical depression as it moved near an instrumented site in Hunstville, AL. The outer rain bands lasted 18 h (03:00 to 21:00 UTC on 08 October 2017) and a 2D-video disdrometer (2DVD) captured the event which was shallow at times and indicative of pure warm rain processes. The 2DVD measurements are used for 3D reconstruction of drop shapes (including the rotationally asymmetric drops) and the drop-by-drop scattering matrix has been computed using Computer Simulation Technology integral equation solver for drop sizes >2.5 mm. From the scattering matrix elements, the polarimetric radar observables are simulated by integrating over 1 min consecutive segments of the event. These simulated values are compared with dual-polarized C-band radar data located at 15 km range from the 2DVD site to evaluate the contribution of the asymmetric drop shapes, specifically to differential reflectivity. The drop fall velocities and drop horizontal velocities in terms of magnitude and direction, all being derived from each drop image from two orthogonal cameras of the 2DVD, are also considered. Full article
(This article belongs to the Special Issue Electromagetics and Polarimetric Weather Radar)
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22 pages, 18818 KiB  
Article
Large-Eddy Simulations with an Immersed Boundary Method: Pollutant Dispersion over Urban Terrain
by Franck Auguste, Christine Lac, Valery Masson and Daniel Cariolle
Atmosphere 2020, 11(1), 113; https://doi.org/10.3390/atmos11010113 - 18 Jan 2020
Cited by 4 | Viewed by 4344
Abstract
In urban canopies, the variability of pollution may be influenced by the presence of surface heterogeneities like orography and buildings. Using the Meso-NH model enhanced with an immersed boundary method (IBM) to represent accurately the impact of the 3D shape of buildings on [...] Read more.
In urban canopies, the variability of pollution may be influenced by the presence of surface heterogeneities like orography and buildings. Using the Meso-NH model enhanced with an immersed boundary method (IBM) to represent accurately the impact of the 3D shape of buildings on the flow, large-eddy simulations are performed over city of Toulouse (France) with the dispersion of a plume following a plant explosion on 21 September 2001. The event is characterized by a large quantity of nitrogen dioxide released in a vertical column after the explosion, quickly dispersed by a moderate wind prevailing in the lower atmospheric layers. Assuming a passive pollutant, the model develops a realistic plume dispersion. A sensitivity analysis of the advection scheme to the spread is presented. The limited population’s exposure to pollution developed by the model appears in good agreement with previous health studies. Beyond this case, IBM is a promising way to represent flow interaction with buildings and orography in atmospheric models for urban applications. Full article
(This article belongs to the Special Issue Air Pollution and Environment in France)
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14 pages, 2416 KiB  
Article
Carbonaceous Aerosol Emitted from Biofuel Household Stove Combustion in South China
by Xuefang Sang-Arlt, Haoxiang Fu, Yinan Zhang, Xiang Ding, Xinming Wang, Yanan Zhou, Lilin Zou, Georg F. Zellmer and Guenter Engling
Atmosphere 2020, 11(1), 112; https://doi.org/10.3390/atmos11010112 - 17 Jan 2020
Cited by 7 | Viewed by 3966
Abstract
Near-source measurements of smoke emissions from household stove combustion in a rural area of South China were conducted with 7 typical biomass fuels. Particulate matter samples (both PM10 and PM2.5) were analyzed for their carbonaceous components, including organic and elemental [...] Read more.
Near-source measurements of smoke emissions from household stove combustion in a rural area of South China were conducted with 7 typical biomass fuels. Particulate matter samples (both PM10 and PM2.5) were analyzed for their carbonaceous components, including organic and elemental carbon (OC, EC) as well as levoglucosan (molecular tracer of biomass burning), employing thermal-optical and GC-MS analysis. The OC and EC content in PM2.5 and PM10 smoke particles derived from the various types of vegetation showed different patterns with the smallest values observed for straw type fuels. The OC/EC ratios in PM2.5 and PM10 showed an order of straw > hardwood > bamboo > softwood. Mass concentrations of particulate matter emitted from rice straw burning were highest with 12.23 ± 0.87 mg/m3 (PM10) and 9.31 ± 0.81 mg/m3 (PM2.5), while the mass ratios (LG/PM and OC/PM) were lowest among the 7 fuels, indicating that particle emissions from straw burning were higher than those from woody fuels, using similar burning conditions. The levoglucosan emission ratios were rather high and this single most abundant organic species was mainly present in the fine particle mode. Linear correlation analysis showed a strong relationship between levoglucosan and EC emissions. Full article
(This article belongs to the Special Issue Ambient Aerosol Measurements in Different Environments)
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17 pages, 7922 KiB  
Article
The Development of a Quantitative Precipitation Forecast Correction Technique Based on Machine Learning for Hydrological Applications
by Chul-Min Ko, Yeong Yun Jeong, Young-Mi Lee and Byung-Sik Kim
Atmosphere 2020, 11(1), 111; https://doi.org/10.3390/atmos11010111 - 16 Jan 2020
Cited by 23 | Viewed by 5378
Abstract
This study aimed to enhance the accuracy of extreme rainfall forecast, using a machine learning technique for forecasting hydrological impact. In this study, machine learning with XGBoost technique was applied for correcting the quantitative precipitation forecast (QPF) provided by the Korea Meteorological Administration [...] Read more.
This study aimed to enhance the accuracy of extreme rainfall forecast, using a machine learning technique for forecasting hydrological impact. In this study, machine learning with XGBoost technique was applied for correcting the quantitative precipitation forecast (QPF) provided by the Korea Meteorological Administration (KMA) to develop a hydrological quantitative precipitation forecast (HQPF) for flood inundation modeling. The performance of machine learning techniques for HQPF production was evaluated with a focus on two cases: one for heavy rainfall events in Seoul and the other for heavy rainfall accompanied by Typhoon Kong-rey (1825). This study calculated the well-known statistical metrics to compare the error derived from QPF-based rainfall and HQPF-based rainfall against the observational data from the four sites. For the heavy rainfall case in Seoul, the mean absolute errors (MAE) of the four sites, i.e., Nowon, Jungnang, Dobong, and Gangnam, were 18.6 mm/3 h, 19.4 mm/3 h, 48.7 mm/3 h, and 19.1 mm/3 h for QPF and 13.6 mm/3 h, 14.2 mm/3 h, 33.3 mm/3 h, and 12.0 mm/3 h for HQPF, respectively. These results clearly indicate that the machine learning technique is able to improve the forecasting performance for localized rainfall. In addition, the HQPF-based rainfall shows better performance in capturing the peak rainfall amount and spatial pattern. Therefore, it is considered that the HQPF can be helpful to improve the accuracy of intense rainfall forecast, which is subsequently beneficial for forecasting floods and their hydrological impacts. Full article
(This article belongs to the Special Issue Radar Hydrology and QPE Uncertainties)
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17 pages, 2795 KiB  
Article
Hybrid Ventilation System and Soft-Sensors for Maintaining Indoor Air Quality and Thermal Comfort in Buildings
by Nivetha Vadamalraj, Kishor Zingre, Subathra Seshadhri, Pandarasamy Arjunan and Seshadhri Srinivasan
Atmosphere 2020, 11(1), 110; https://doi.org/10.3390/atmos11010110 - 16 Jan 2020
Cited by 11 | Viewed by 7061
Abstract
Maintaining both indoor air quality (IAQ) and thermal comfort in buildings along with optimized energy consumption is a challenging problem. This investigation presents a novel design for hybrid ventilation system enabled by predictive control and soft-sensors to achieve both IAQ and thermal comfort [...] Read more.
Maintaining both indoor air quality (IAQ) and thermal comfort in buildings along with optimized energy consumption is a challenging problem. This investigation presents a novel design for hybrid ventilation system enabled by predictive control and soft-sensors to achieve both IAQ and thermal comfort by combining predictive control with demand controlled ventilation (DCV). First, we show that the problem of maintaining IAQ, thermal comfort and optimal energy is a multi-objective optimization problem with competing objectives, and a predictive control approach is required to smartly control the system. This leads to many implementation challenges which are addressed by designing a hybrid ventilation scheme supported by predictive control and soft-sensors. The main idea of the hybrid ventilation system is to achieve thermal comfort by varying the ON/OFF times of the air conditioners to maintain the temperature within user-defined bands using a predictive control and IAQ is maintained using Healthbox 3.0, a DCV device. Furthermore, this study also designs soft-sensors by combining the Internet of Things (IoT)-based sensors with deep-learning tools. The hardware realization of the control and IoT prototype is also discussed. The proposed novel hybrid ventilation system and the soft-sensors are demonstrated in a real research laboratory, i.e., Center for Research in Automatic Control Engineering (C-RACE) located at Kalasalingam University, India. Our results show the perceived benefits of hybrid ventilation, predictive control, and soft-sensors. Full article
(This article belongs to the Special Issue Indoor Thermal Comfort)
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17 pages, 5035 KiB  
Article
A Markov Chain-Based Bias Correction Method for Simulating the Temporal Sequence of Daily Precipitation
by Han Liu, Jie Chen, Xun-Chang Zhang, Chong-Yu Xu and Yu Hui
Atmosphere 2020, 11(1), 109; https://doi.org/10.3390/atmos11010109 - 16 Jan 2020
Cited by 9 | Viewed by 3844
Abstract
Bias correction methods are routinely used to correct climate model outputs for hydrological and agricultural impact studies. Even though superior bias correction methods can correct the distribution of daily precipitation amounts, as well as the wet-day frequency, they usually fail to correct the [...] Read more.
Bias correction methods are routinely used to correct climate model outputs for hydrological and agricultural impact studies. Even though superior bias correction methods can correct the distribution of daily precipitation amounts, as well as the wet-day frequency, they usually fail to correct the temporal sequence or structure of precipitation occurrence. To solve this problem, we presented a hybrid bias correction method for simulating the temporal sequence of daily precipitation occurrence. We did this by combining a first-order two-state Markov chain with a quantile-mapping (QM) based bias correction method. Specifically, a QM-based method was used to correct the distributional attributes of daily precipitation amounts and the wet-day frequency simulated by climate models. Then, the sequence of precipitation occurrence was simulated using the first-order two-state Markov chain with its parameters adjusted based on linear relationships between QM-corrected mean monthly precipitation and the transition probabilities of precipitation occurrence. The proposed Markov chain-based bias correction (MCBC) method was compared with the QM-based method with respect to reproducing the temporal structure of precipitation occurrence over 10 meteorological stations across China. The results showed that the QM-based method was unable to correct the temporal sequence, with the cumulative frequency of wet- and dry-spell length being considerably underestimated for most stations. The MCBC method can could reproduce the temporal sequence of precipitation occurrence, with the generated cumulative frequency of wet- and dry-spell lengths fitting that of the observation well. The proposed method also performed reasonably well with respect to reproducing the mean, standard deviation, and the longest length of observed wet- and dry-spells. Overall, the MCBC method can simulate the temporal sequence of precipitation occurrence, along with correcting the distributional attributes of precipitation amounts. This method can be used with crop and hydrological models in climate change impact studies at the field and small watershed scales. Full article
(This article belongs to the Special Issue Climate Data for Agricultural Applications: Downscaling and Scenarios)
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20 pages, 6058 KiB  
Article
The Climatology and Trend of Surface Wind Speed over Antarctica and the Southern Ocean and the Implication to Wind Energy Application
by Lejiang Yu, Shiyuan Zhong and Bo Sun
Atmosphere 2020, 11(1), 108; https://doi.org/10.3390/atmos11010108 - 16 Jan 2020
Cited by 30 | Viewed by 8206
Abstract
Surface wind trends and variability over Antarctica and the Southern Ocean and their implications to wind energy in the region are analyzed using the gridded ERA-Interim reanalysis data between 1979 and 2017 and the Self-Organizing Map (SOM) technique. In general, surface winds are [...] Read more.
Surface wind trends and variability over Antarctica and the Southern Ocean and their implications to wind energy in the region are analyzed using the gridded ERA-Interim reanalysis data between 1979 and 2017 and the Self-Organizing Map (SOM) technique. In general, surface winds are stronger over the coastal regions of East Antarctica and the Transantarctic Mountains and weaker over the Ross and Ronne ice shelves and the Antarctic Peninsula; and stronger in winter and weaker in summer. Winds in the southern Indian and Pacific Oceans and along coastal regions exhibit a strong interannual variability that appears to be correlated to the Antarctic Oscillation (AAO) index. A significantly positive trend in surface wind speeds is found across most regions and about 20% and 17% of the austral autumn and summer wind trends, respectively, and less than 1% of the winter and spring wind trends may be explained by the trends in the AAO index. Except for the Antarctic Peninsula, Ronne and Ross ice shelves, and small areas in the interior East Antarctica, most of the continent is found to be suitable for the development of wind power. Full article
(This article belongs to the Special Issue Interaction Processes between Atmosphere and Sea-Land-Snow-Ice in the Polar Regions)
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15 pages, 3149 KiB  
Article
Characteristics of Surface Ozone in Five Provincial Capital Cities of China during 2014–2015
by Xin Wang, Zhenxing Shen, Zhuoyue Tang, Guohui Li, Yali Lei, Qian Zhang, Yaling Zeng, Hongmei Xu, Junji Cao and Renjian Zhang
Atmosphere 2020, 11(1), 107; https://doi.org/10.3390/atmos11010107 - 16 Jan 2020
Cited by 11 | Viewed by 3282
Abstract
Ozone (O3) pollution has become an increasing concern in China since elevated surface O3 concentrations were observed in recent years. In this study, five provincial cities (Beijing, Shanghai, Guangzhou, Xi’an, and Hefei) located in different regions of China were selected [...] Read more.
Ozone (O3) pollution has become an increasing concern in China since elevated surface O3 concentrations were observed in recent years. In this study, five provincial cities (Beijing, Shanghai, Guangzhou, Xi’an, and Hefei) located in different regions of China were selected to study the spatiotemporal variations and affecting factors of O3 concentrations during 2014–2015. Beijing, Shanghai, and Guangzhou had suffered more severe O3 pollution, yet Beijing had the highest number of days that exceeded the Chinese MDA8 (maximum daily 8 h average) standard of 160 µg m−3. MDA8 O3 exhibited different seasonal patterns among the five cities. In Beijing and Xi’an, MDA8 O3 showed the highest in summer and lowest in winter. Guangzhou also had the highest O3 concentration in summer, but had similar levels in other three seasons. The O3 levels were similarly high in Shanghai during spring, summer, and autumn, while in Hefei, O3 concentration peaked in autumn. No significant difference between weekend and weekday O3 levels was observed in all the five cities. The diurnal cycle reached a maximum in the afternoon and a minimum in the early morning, which was consistent in the five cities. Correlation analyses showed that the associations between O3 and the other five criteria air pollutants, as well as meteorological parameters, were substantially different among the five cities. Air mass cluster analyses during episodic days revealed that the short-distance transport of O3 and its precursors had a greater impact for high O3 pollution in the five cities. Overall, our results demonstrate that O3 pollution exhibited great divergence among different regions and thus region-oriented control measures are suggested to reduce O3 pollution in China. Full article
(This article belongs to the Section Air Quality)
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17 pages, 1084 KiB  
Article
Determining the Effect of Extreme Weather Events on Human Participation in Recreation and Tourism: A Case Study of the Toronto Zoo
by Micah J. Hewer
Atmosphere 2020, 11(1), 99; https://doi.org/10.3390/atmos11010099 - 15 Jan 2020
Cited by 14 | Viewed by 4491
Abstract
This study devises a novel approach for defining extreme weather events and assessing their effects on human participation in recreation and tourism, based on a case study of attendance at the Toronto Zoo (Toronto, ON, Canada). Daily zoo attendance data from 1999 to [...] Read more.
This study devises a novel approach for defining extreme weather events and assessing their effects on human participation in recreation and tourism, based on a case study of attendance at the Toronto Zoo (Toronto, ON, Canada). Daily zoo attendance data from 1999 to 2018 was obtained and analyzed in connection with daily weather data from local weather stations for the maximum temperature, minimum temperature, total precipitation, and maximum wind speed. The “climatic distance” method, used for evaluating representative weather stations for case studies in applied climatology, was employed to rank and select surrounding weather stations that most accurately captured daily weather observations recorded at the Toronto Zoo from 1990 to 1992. Extreme weather events can be defined as lying in the outermost (most unusual) 10 percent of a place’s history. Using this definition as the foundation, a percentile approach was developed to identify and assess the effects of extreme weather events across the following thresholds: the 99th percentile, the 95th percentile, and the 90th percentile, as well as less than the 1st percentile, less than the 5th percentile, and less than the 10th percentile. Additionally, revealed, theoretical, and binary thresholds were also assessed to verify their merit and determine their effects, and were compared to the extreme weather events defined by the percentiles approach. Overall, extreme daily weather events had statistically significant negative effects on zoo attendance in Toronto, apart from a few cases, such as the positive effect of usually warm daytime temperatures in the winter and usually cool nighttime temperatures in the summer. The most influential weather event across all seasons was extremely hot temperatures, which has important implications for climate change impact assessments. Full article
(This article belongs to the Special Issue Tourism Climatology: Past, Present and Future)
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12 pages, 2508 KiB  
Article
Sodium Resonance Wind-Temperature Lidar at PFRR: Initial Observations and Performance
by Jintai Li, Bifford P. Williams, Jennifer H. Alspach and Richard L. Collins
Atmosphere 2020, 11(1), 98; https://doi.org/10.3390/atmos11010098 - 15 Jan 2020
Cited by 6 | Viewed by 3476
Abstract
A narrowband sodium resonance wind-temperature lidar (SRWTL) has been deployed at Poker Flat Research Range, Chatanika, Alaska (PFRR, 65° N, 147° W). Based on the Weber narrowband SRWTL, the PFRR SRWTL transmitter was upgraded with a state-of-the-art solid-state tunable diode laser as the [...] Read more.
A narrowband sodium resonance wind-temperature lidar (SRWTL) has been deployed at Poker Flat Research Range, Chatanika, Alaska (PFRR, 65° N, 147° W). Based on the Weber narrowband SRWTL, the PFRR SRWTL transmitter was upgraded with a state-of-the-art solid-state tunable diode laser as the seed laser. The PFRR SRWTL currently makes simultaneous measurements in the zenith and 20° off-zenith towards the north with two transmitted beams and two telescopes. Initial results for both nighttime and daytime measurements are presented. We review the performance of the PFRR SRWTL in terms of seven previous and currently operating SRWTLs. The transmitted power from the pulsed dye amplifier (PDA) is comparable with other SRWTL systems (900 mW). However, while the efficiency of the seeding and frequency shifting is comparable to other SRWTLs the efficiency of the pumping is lower. The uncertainties of temperature and wind measurements induced by photon noise at the peak of the layer with a 5 min, 1 km resolution are estimated to be ~1 K and 2 m/s for nighttime conditions, and 10 K and 6 m/s for daytime conditions. The relative efficiency of the zenith receiver is comparable to other SRWTLs (90–97%), while the efficiency of the north off-zenith receiver needs further optimization. An upgrade of the PFRR SRWTL to a full three-beam system with zenith, northward and eastward measurements is in progress. Full article
(This article belongs to the Special Issue Advances in Atmospheric Lidar Remote Sensing)
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14 pages, 4405 KiB  
Article
Assessment of a Real-Time Prediction Method for High Clothing Thermal Insulation Using a Thermoregulation Model and an Infrared Camera
by Kyungsoo Lee, Haneul Choi, Hyungkeun Kim, Daeung Danny Kim and Taeyeon Kim
Atmosphere 2020, 11(1), 106; https://doi.org/10.3390/atmos11010106 - 15 Jan 2020
Cited by 21 | Viewed by 6189
Abstract
For evaluating the thermal comfort of occupants, human factors such as clothing thermal insulation (clo level) and metabolic rate (Met) are one of the important parameters as well as environmental factors such as air temperature (Ta) and humidity. In general, a fixed clo [...] Read more.
For evaluating the thermal comfort of occupants, human factors such as clothing thermal insulation (clo level) and metabolic rate (Met) are one of the important parameters as well as environmental factors such as air temperature (Ta) and humidity. In general, a fixed clo level is commonly used for controlling heating, ventilation, and air conditioning using the thermal comfort index. However, a fixed clo level can lead to errors for estimating the thermal comfort of occupants, because clo levels of occupants can vary with time and by season. The present study assesses a method for predicting the clo level of occupants using a thermoregulation model and an infrared (IR) camera. The Tanabe model and the Fanger model were used as the thermoregulation models, and the predicted performance for high clo level (winter clothing) was compared. The skin and clothing temperatures of eight subjects using a non-contact IR camera were measured in a climate chamber. In addition, the measured values were used for the thermoregulation models to predict the clo levels. As a result, the Tanabe model showed a better performance than the Fanger model for predicting clo levels. In addition, all models tended to predict a clo level higher than the traditional method. Full article
(This article belongs to the Special Issue Indoor Thermal Comfort)
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20 pages, 6105 KiB  
Article
Association of Diurnal Rainfall in Northeastern Tibetan Plateau with the Retreat of the South Asian High
by Lin Zhao, S.-Y. Simon Wang, Chi-Hua Wu, Sebastian Los, Shihua Lyu, Xianhong Meng, Lijuan Wen, Siqiong Luo, Yinhuan Ao and Zhaoguo Li
Atmosphere 2020, 11(1), 105; https://doi.org/10.3390/atmos11010105 - 15 Jan 2020
Cited by 6 | Viewed by 3749
Abstract
The characteristics of intense diurnal precipitation occurring beneath the South Asian High (SAH) are diagnosed in the summer monsoon season from 2010 to 2015 using observational data. The diagnostics indicate that summer nighttime rainfall events in the northeastern Tibetan Plateau can intensify towards [...] Read more.
The characteristics of intense diurnal precipitation occurring beneath the South Asian High (SAH) are diagnosed in the summer monsoon season from 2010 to 2015 using observational data. The diagnostics indicate that summer nighttime rainfall events in the northeastern Tibetan Plateau can intensify towards the end of the monsoon period. By defining a transition index to identify the transition day during which the episodes of diurnal convection start to decline, daily thermodynamic properties and precipitation from each year were composited before and after the transition date. The analysis reveals that warmer air, increased moisture, and stronger upward velocity are present in the atmosphere before the transition day, potentially elevating nighttime convective precipitation. Enhanced upward velocity that is present through the two months prior to transition date coincides with the timing of the peak SAH, while weakened upward velocity afterwards coincides with its subsequent retreat. The large-scale lift due to terrain-ambient air interaction underneath the SAH and the increased moisture content can enhance the potential for diurnal convection, which lends support to the nighttime peak of rainfall. This feature persists until the transition date, after which the SAH starts to retreat. Full article
(This article belongs to the Section Meteorology)
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25 pages, 5772 KiB  
Article
Heavy Rainfall Events and Mass Movements in the Funchal Area (Madeira, Portugal): Spatial Analysis and Susceptibility Assessment
by Sérgio Lopes, Marcelo Fragoso and António Lopes
Atmosphere 2020, 11(1), 104; https://doi.org/10.3390/atmos11010104 - 15 Jan 2020
Cited by 6 | Viewed by 5609
Abstract
The article presents new information on the spatial distribution of intense rainfall and a new map of susceptibility to the formation of mass movements in the mountainous streams of the municipality of Funchal, the capital of the Autonomous Region of Madeira, an archipelago [...] Read more.
The article presents new information on the spatial distribution of intense rainfall and a new map of susceptibility to the formation of mass movements in the mountainous streams of the municipality of Funchal, the capital of the Autonomous Region of Madeira, an archipelago of Portugal. The methodology that was adopted is based on the spatial analysis of weighted overlap of variables, with influence in the occurrence of hydro-geomorphological processes that are at the origin of catastrophic events, marked by the mobilization of solid material towards and along the fluvial channels. Intense precipitations are effectively the main triggering factor of mass movements, which is why their statistical characteristics and local contrasts are analyzed, to integrate this layer of information into the new susceptibility assessment model of mass movements produced in this article. This type of spatialized information is of strategic importance to support the planning of urban expansion, which requires a land use management practice in accordance with the existing risk in the Madeira Island. Full article
(This article belongs to the Special Issue Climatological and Hydrological Processes in Mountain Regions)
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12 pages, 3407 KiB  
Article
Incorporation of Remote PM2.5 Concentrations into the Downscaler Model for Spatially Fused Air Quality Surfaces
by Brett Gantt, Kelsey McDonald, Barron Henderson and Elizabeth Mannshardt
Atmosphere 2020, 11(1), 103; https://doi.org/10.3390/atmos11010103 - 15 Jan 2020
Cited by 5 | Viewed by 3080
Abstract
The United States Environmental Protection Agency (EPA) has implemented a Bayesian spatial data fusion model called the Downscaler (DS) model to generate daily air quality surfaces for PM2.5 across the contiguous U.S. Previous implementations of DS relied on monitoring data from EPA’s [...] Read more.
The United States Environmental Protection Agency (EPA) has implemented a Bayesian spatial data fusion model called the Downscaler (DS) model to generate daily air quality surfaces for PM2.5 across the contiguous U.S. Previous implementations of DS relied on monitoring data from EPA’s Air Quality System (AQS) network, which is largely concentrated in urban areas. In this work, we introduce to the DS modeling framework an additional PM2.5 input dataset from the Interagency Monitoring of Protected Visual Environments (IMPROVE) network located mainly in remote sites. In the western U.S. where IMPROVE sites are relatively dense (compared to the eastern U.S.), the inclusion of IMPROVE PM2.5 data to the DS model runs reduces predicted annual averages and 98th percentile concentrations by as much as 1.0 and 4 μg m−3, respectively. Some urban areas in the western U.S., such as Denver, Colorado, had moderate increases in the predicted annual average concentrations, which led to a sharpening of the gradient between urban and remote areas. Comparison of observed and DS-predicted concentrations for the grid cells containing IMPROVE and AQS sites revealed consistent improvement at the IMPROVE sites but some degradation at the AQS sites. Cross-validation results of common site-days withheld in both simulations show a slight reduction in the mean bias but a slight increase in the mean square error when the IMPROVE data is included. These results indicate that the output of the DS model (and presumably other Bayesian data fusion models) is sensitive to the addition of geographically distinct input data, and that the application of such models should consider the prediction domain (national or urban focused) when deciding to include new input data. Full article
(This article belongs to the Section Air Quality)
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18 pages, 6747 KiB  
Article
Low Polluting Building Materials and Ventilation for Good Air Quality in Residential Buildings: A Cost–Benefit Study
by Francesco Babich, Ingrid Demanega, Francesca Avella and Annamaria Belleri
Atmosphere 2020, 11(1), 102; https://doi.org/10.3390/atmos11010102 - 15 Jan 2020
Cited by 9 | Viewed by 5417
Abstract
Nowadays, people spend an average of 87% of their time inside buildings, and about 69% at home. Hence, it is essential to ensure the highest possible level of indoor air quality (IAQ). Providing that the quality of the outdoor air is acceptable, the [...] Read more.
Nowadays, people spend an average of 87% of their time inside buildings, and about 69% at home. Hence, it is essential to ensure the highest possible level of indoor air quality (IAQ). Providing that the quality of the outdoor air is acceptable, the IAQ level is improved by increasing the ventilation rates. However, this means that a larger volume of air must be cooled down or warmed up to ensure the same level of thermal comfort. The aim of this study was to conduct a cost–benefit analysis of the IAQ in residential buildings. A case-study building was defined, and three sets of materials with different pollution emission levels were chosen: High, low, and very low. For each option, the ventilation rates required to have the same IAQ level were calculated, and the consequent energy consumption and costs were estimated by means of dynamic thermal simulation. The results show the range of the initial capital cost that could be compensated for by lower running costs, and the effect of each energy and economic input assumption on the appraisal of the affordable capital cost. In the discussion, insights into the IAQ co-benefits are also given. Full article
(This article belongs to the Special Issue Green Buildings and Indoor Air Quality)
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19 pages, 4853 KiB  
Article
Fine-Scale Columnar and Surface NOx Concentrations over South Korea: Comparison of Surface Monitors, TROPOMI, CMAQ and CAPSS Inventory
by Hyun Cheol Kim, Soontae Kim, Sang-Hyun Lee, Byeong-Uk Kim and Pius Lee
Atmosphere 2020, 11(1), 101; https://doi.org/10.3390/atmos11010101 - 15 Jan 2020
Cited by 25 | Viewed by 6175
Abstract
Fine-scale nitrogen oxide (NOx) concentrations over South Korea are examined using surface observations, satellite data and high-resolution model simulations based on the latest emission inventory. While accurate information on NOx emissions in South Korea is crucial to understanding regional air [...] Read more.
Fine-scale nitrogen oxide (NOx) concentrations over South Korea are examined using surface observations, satellite data and high-resolution model simulations based on the latest emission inventory. While accurate information on NOx emissions in South Korea is crucial to understanding regional air quality in the region, consensus on the validation of NOx emissions is lacking. We investigate the spatial and temporal variation in fine-scale NOx emission sources over South Korea. Surface observations and newly available fine-scale satellite data (TROPOspheric Monitoring Instrument; TROPOMI; 3.5 × 7 km2) are compared with the community multiscale air quality (CMAQ) model based on the clean air policy support system (CAPSS) 2016 emission inventory. The results show that the TROPOMI NO2 column densities agree well with the CMAQ simulations based on CAPSS emissions (e.g., R = 0.96 for June 2018). The surface observations, satellite data and model are consistent in terms of their spatial distribution, the overestimation over the Seoul Metropolitan Area and major point sources; however, the model tends to underestimate the surface concentrations during the cold season. Full article
(This article belongs to the Special Issue Recent Advances of Air Pollution Studies in South Korea)
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11 pages, 1592 KiB  
Article
Computational Study of the Dissociation Reactions of Secondary Ozonide
by Mansour H. Almatarneh, Shefa’ F. Alrebei, Mohammednoor Altarawneh, Yuming Zhao and Abd Al-Aziz Abu-Saleh
Atmosphere 2020, 11(1), 100; https://doi.org/10.3390/atmos11010100 - 15 Jan 2020
Cited by 4 | Viewed by 4070
Abstract
This contribution presents a comprehensive computational study on the reactions of secondary ozonide (SOZ) with ammonia and water molecules. The mechanisms were studied in both a vacuum and the aqueous medium. All the molecular geometries were optimized using the B3LYP functional in conjunction [...] Read more.
This contribution presents a comprehensive computational study on the reactions of secondary ozonide (SOZ) with ammonia and water molecules. The mechanisms were studied in both a vacuum and the aqueous medium. All the molecular geometries were optimized using the B3LYP functional in conjunction with several basis sets. M06-2X, APFD, and ωB97XD functionals with the full basis set were also used. In addition, single-point energy calculations were performed with the G4MP2 and G3MP2 methods. Five different mechanistic pathways were studied for the reaction of SOZ with ammonia and water molecules. The most plausible mechanism for the reaction of SOZ with ammonia yields HC(O)OH, NH3, and HCHO as products, with ammonia herein acting as a mediator. This pathway is exothermic and exergonic, with an overall barrier height of only 157 kJ mol−1 using the G3MP2 method. All the reaction pathways between SOZ and water molecules are endothermic and endergonic reactions. The most likely reaction pathway for the reaction of SOZ with water involves a water dimer, in which the second water molecule acts as a mediator, with an overall barrier height of only 135 kJ mol−1 using the G3MP2 method. Solvent effects were found to incur a significant reduction in activation energies. When the second H2O molecule acts as a mediator in the reaction of SOZ with water, the barrier height of the rate-determining step state decreases significantly. Full article
(This article belongs to the Section Aerosols)
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14 pages, 3406 KiB  
Article
Ice Hydrometeor Shape Estimations Using Polarimetric Operational and Research Radar Measurements
by Sergey Y. Matrosov
Atmosphere 2020, 11(1), 97; https://doi.org/10.3390/atmos11010097 - 14 Jan 2020
Cited by 8 | Viewed by 3635
Abstract
A polarimetric radar method to estimate mean shapes of ice hydrometeors was applied to several snowfall and ice cloud events observed by operational and research weather radars. The hydrometeor shape information is described in terms of their aspect ratios, r, which represent [...] Read more.
A polarimetric radar method to estimate mean shapes of ice hydrometeors was applied to several snowfall and ice cloud events observed by operational and research weather radars. The hydrometeor shape information is described in terms of their aspect ratios, r, which represent the ratio of particle minor and major dimensions. The method is based on the relations between depolarization ratio (DR) estimates and aspect ratios. DR values, which are a proxy for circular depolarization ratio, were reconstructed from radar variables of reflectivity factor, Ze, differential reflectivity, ZDR, and copolar correlation coefficient ρhv, which are available from radar systems operating in either simultaneous or alternate transmutation of horizontally and vertically polarized signals. DR-r relations were developed for retrieving aspect ratios and their sensitivity to different assumptions and model uncertainties were discussed. To account for changing particle bulk density, which is a major contributor to the retrieval uncertainty, an approach is suggested to tune the DR-r relations using reflectivity-based estimates of characteristic hydrometeor size. The analyzed events include moderate snowfall observed by an operational S-band weather radar and a precipitating ice cloud observed by a scanning Ka-band cloud radar at an Arctic location. Uncertainties of the retrievals are discussed. Full article
(This article belongs to the Special Issue Electromagetics and Polarimetric Weather Radar)
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17 pages, 6325 KiB  
Article
UV Index Forecasting under the Influence of Desert Dust: Evaluation against Surface and Satellite-Retrieved Data
by Dillan Raymond Roshan, Muammer Koc, Amir Abdallah, Luis Martin-Pomares, Rima Isaifan and Christos Fountoukis
Atmosphere 2020, 11(1), 96; https://doi.org/10.3390/atmos11010096 - 13 Jan 2020
Cited by 23 | Viewed by 12267
Abstract
Human exposure to healthy doses of UV radiation is required for vitamin D synthesis, but exposure to excessive UV irradiance leads to several harmful impacts ranging from premature wrinkles to dangerous skin cancer. However, for countries located in the global dust belt, accurate [...] Read more.
Human exposure to healthy doses of UV radiation is required for vitamin D synthesis, but exposure to excessive UV irradiance leads to several harmful impacts ranging from premature wrinkles to dangerous skin cancer. However, for countries located in the global dust belt, accurate estimation of the UV irradiance is challenging due to a strong impact of desert dust on incoming solar radiation. In this work, a UV Index forecasting capability is presented, specifically developed for dust-rich environments, that combines the use of ground-based measurements of broadband irradiances UVA (320–400 nm) and UVB (280–315 nm), NASA OMI Aura satellite-retrieved data and the meteorology-chemistry mesoscale model WRF-Chem. The forecasting ability of the model is evaluated for clear sky days as well as during the influence of dust storms in Doha, Qatar. The contribution of UV radiation to the total incoming global horizontal irradiance (GHI) ranges between 5% and 7% for UVA and 0.1% and 0.22% for UVB. The UVI forecasting performance of the model is quite encouraging with an absolute average error of less than 6% and a correlation coefficient of 0.93. In agreement with observations, the model predicts that the UV Index at local noontime can drop from 10–11 on clear sky days to approximately 6–7 during typical dusty conditions in the Arabian Peninsula—an effect similar to the presence of extensive cloud cover. Full article
(This article belongs to the Section Aerosols)
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14 pages, 2099 KiB  
Article
An Investigation of Parameter Sensitivity of Minimum Complexity Earth Simulator
by Jiewei Chen, Huijuan Cui, Yangyang Xu and Quansheng Ge
Atmosphere 2020, 11(1), 95; https://doi.org/10.3390/atmos11010095 - 13 Jan 2020
Cited by 5 | Viewed by 3311
Abstract
Climate change, induced by human greenhouse gas emission, has already influenced the environment and society. To quantify the impact of human activity on climate change, scientists have developed numerical climate models to simulate the evolution of the climate system, which often contains many [...] Read more.
Climate change, induced by human greenhouse gas emission, has already influenced the environment and society. To quantify the impact of human activity on climate change, scientists have developed numerical climate models to simulate the evolution of the climate system, which often contains many parameters. The choice of parameters is of great importance to the reliability of the simulation. Therefore, parameter sensitivity analysis is needed to optimize the parameters for the model so that the physical process of nature can be reasonably simulated. In this study, we analyzed the parameter sensitivity of a simple carbon-cycle energy balance climate model, called the Minimum Complexity Earth Simulator (MiCES), in different periods using a multi-parameter sensitivity analysis method and output measurement method. The results show that the seven parameters related to heat and carbon transferred are most sensitive among all 37 parameters. Then uncertainties of the above key parameters are further analyzed by changing the input emission and temperature, providing reference bounds of parameters with 95% confidence intervals. Furthermore, we found that ocean heat capacity will be more sensitive if the simulation time becomes longer, indicating that ocean influence on climate is stronger in the future. Full article
(This article belongs to the Section Climatology)
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22 pages, 3342 KiB  
Article
PM10 and PM2.5 Qualitative Source Apportionment Using Selective Wind Direction Sampling in a Port-Industrial Area in Civitavecchia, Italy
by Maria Eleonora Soggiu, Marco Inglessis, Roberta Valentina Gagliardi, Gaetano Settimo, Giovanni Marsili, Ivan Notardonato and Pasquale Avino
Atmosphere 2020, 11(1), 94; https://doi.org/10.3390/atmos11010094 - 13 Jan 2020
Cited by 21 | Viewed by 4893
Abstract
The possibility to discriminate between different emission sources and between natural and anthropogenic contributions is a key issue for planning efficient air pollution reduction and mitigation strategies. Moreover, the knowledge of the particulate matter (PM) chemical composition for the different size fractions is [...] Read more.
The possibility to discriminate between different emission sources and between natural and anthropogenic contributions is a key issue for planning efficient air pollution reduction and mitigation strategies. Moreover, the knowledge of the particulate matter (PM) chemical composition for the different size fractions is recognized as increasingly important, in particular with respect to health effects of exposed population. This study is focused on the characterization of PM10 and PM2.5 main sources located in the Civitavecchia harbor-industrial area (Central Italy), namely a large coal-fired power plant, a natural gas power plant, the harbor area, the vehicular traffic (due to both the local traffic and the highway crossing the area) and small industrial activities. The approach was based on PM10/PM2.5 samples monthly collected for one year and a further relative chemical characterization of organic and inorganic fractions. Wind-select sensors, allowing a selective PM10 and PM2.5 sampling downwind to specific emission sources, were used for the overall sampling. This methodology manages to explain specific emission patterns and to assess the concentration levels of the micro pollutants emitted by local sources and particularly toxic for health. A descriptive statistical analysis of data was performed, also verifying the occurrence of legislative threshold exceedances. Moreover, in order to highlight the contribution of specific sources, the differences in the measured micro pollutants concentrations between wind directions, PM size fractions and sampling sites have been investigated, as well as the seasonal trends of pollutants concentrations. These results allow to highlight that the applied methodology represents a valid support in source apportionment studies. Full article
(This article belongs to the Special Issue Exposure Assessment of Air Pollution)
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11 pages, 3936 KiB  
Article
Changes in Tropical-Cyclone Translation Speed over the Western North Pacific
by Dongna Zhang, Han Zhang, Jiayu Zheng, Xuhua Cheng, Di Tian and Dake Chen
Atmosphere 2020, 11(1), 93; https://doi.org/10.3390/atmos11010093 - 13 Jan 2020
Cited by 21 | Viewed by 5448
Abstract
The trend of tropical-cyclone (TC) translation speed is a hot topic recently. Changes in TC translation speed during 1949–2017 over the western North Pacific are analyzed using two best-track datasets here. The TC translation speed decreased during 1949–2017, but there was no significant [...] Read more.
The trend of tropical-cyclone (TC) translation speed is a hot topic recently. Changes in TC translation speed during 1949–2017 over the western North Pacific are analyzed using two best-track datasets here. The TC translation speed decreased during 1949–2017, but there was no significant trend after 1981. The TC translation speed also changes with latitude and intensity. In the tropical ocean, TC translation speed decreased by 5.9% during 69-year recording period. North of 23.5° N, the changes in translation speed is highly consistent with the latitude of TC occurrence. The translation speed of tropical depressions showed no significant trend during the period 1949–2017, but the translation speed of typhoons decreased over the 69-year recording period. The period 1949–1981 contributed most of the slowdown trend. There also was an increase in the frequency of typhoons with translation speed slower than 6 m/s. The decrease of translation speed of typhoons before 1981 was likely caused by the weakening of the summertime tropical circulation. Full article
(This article belongs to the Section Meteorology)
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27 pages, 2357 KiB  
Review
How Can Odors Be Measured? An Overview of Methods and Their Applications
by Carmen Bax, Selena Sironi and Laura Capelli
Atmosphere 2020, 11(1), 92; https://doi.org/10.3390/atmos11010092 - 13 Jan 2020
Cited by 88 | Viewed by 36814
Abstract
In recent years, citizens’ attention towards air quality and pollution has increased significantly, and nowadays, odor pollution related to different industrial activities is recognized as a well-known environmental issue. For this reason, odors are subjected to control and regulation in many countries, and [...] Read more.
In recent years, citizens’ attention towards air quality and pollution has increased significantly, and nowadays, odor pollution related to different industrial activities is recognized as a well-known environmental issue. For this reason, odors are subjected to control and regulation in many countries, and specific methods for odor measurement have been developed and standardized over the years. This paper, conceived within the H2020 D-NOSES project, summarizes odor measurement techniques, highlighting their applicability, advantages, and limits, with the aim of providing experienced as well as non-experienced users a useful tool that can be consulted in the management of specific odor problems for evaluating and identifying the most suitable approach. The paper also presents relevant examples of the application of the different methods discussed, thereby mainly referring to scientific articles published over the last 10 years. Full article
(This article belongs to the Special Issue Environmental Odour: Emission, Dispersion, and the Assessment of Annoyance)
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