Atmosphere

12 pages, 10892 KiB

Open AccessEditor’s ChoiceArticle

Air Pollution and Long Term Mental Health

by Younoh Kim, James Manley and Vlad Radoias

Atmosphere 2020, 11(12), 1355; https://doi.org/10.3390/atmos11121355 - 14 Dec 2020

Cited by 24 | Viewed by 4505

We study the long-term consequences of air pollution on mental health, using a natural experiment in Indonesia. We find that exposure to severe air pollution has significant and persistent consequences on mental health. An extra standard deviation in the pollution index raises the [...] Read more.

We study the long-term consequences of air pollution on mental health, using a natural experiment in Indonesia. We find that exposure to severe air pollution has significant and persistent consequences on mental health. An extra standard deviation in the pollution index raises the probability of clinical depression measured 10 years past exposure by almost 1%. Women in particular seem to be more affected, but some effects persist for men as well. Pollution exposure increases the likelihood of clinical depression for women and also the severity of depressive symptoms for both sexes. It is not clear if men are more resistant to pollution or they simply recover faster from it. Education, perceived economic status, and marriage seem to be the best mitigators for these negative effects. Full article

(This article belongs to the Special Issue Contributions of Aerosol Sources to Health Impacts)

26 pages, 7095 KiB

Open AccessEditor’s ChoiceArticle

The Microscale Urban Surface Energy (MUSE) Model for Real Urban Application

by Doo-Il Lee and Sang-Hyun Lee

Atmosphere 2020, 11(12), 1347; https://doi.org/10.3390/atmos11121347 - 12 Dec 2020

Cited by 5 | Viewed by 2645

Abstract

Urban atmospheric environmental issues are commonly associated with the physical processes of urban surfaces. Much progress has been made on the building-resolving microscale atmospheric models, but a realistic representation of the physical processes of urban surfaces on those models is still lacking. This [...] Read more.

Urban atmospheric environmental issues are commonly associated with the physical processes of urban surfaces. Much progress has been made on the building-resolving microscale atmospheric models, but a realistic representation of the physical processes of urban surfaces on those models is still lacking. This study presents a new microscale urban surface energy (MUSE) model for real urban meteorological and environmental applications that is capable of representing the urban radiative, convective, and conductive energy transfer processes along with their interactions, and that is directly compatible with the Cartesian grid microscale atmospheric models. The physical processes of shadow casting and radiative transfers were validated on an analytical accuracy level. The full capability of the model in simulating the three-dimensional surface heterogeneities in a real urban environment was tested for a hot summer day in August 2016 using the field measurements obtained from the Kongju National University campus, South Korea. The validation against the measurements showed that the model is capable of predicting surface temperatures and energy balance fluxes in a patch scale at the heterogeneous urban surfaces by virtue of the interactive representation of the urban physical processes. The excellent performance and flexible grid design emphasize the potential capabilities of the MUSE model for use in urban meteorological and environmental applications through the building-resolving microscale atmospheric models, such as computational fluid dynamics (CFD) and large-eddy simulations (LES). Full article

(This article belongs to the Section Atmospheric Techniques, Instruments, and Modeling)

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17 pages, 5377 KiB

Open AccessEditor’s ChoiceArticle

High Latitude Dust Transport Altitude Pattern Revealed from Deposition on Snow, Svalbard

by Jan Kavan, Kamil Láska, Adam Nawrot and Tomasz Wawrzyniak

Atmosphere 2020, 11(12), 1318; https://doi.org/10.3390/atmos11121318 - 6 Dec 2020

Cited by 8 | Viewed by 3571

Abstract

High Latitude Dust (HLD) deposition in the surface snow layer in two distant locations in Svalbard (Hornsund and Pyramiden) were collected during the June/July 2019 field campaign and examined in the laboratory. Despite the differences in their climate and topography, both locations are [...] Read more.

High Latitude Dust (HLD) deposition in the surface snow layer in two distant locations in Svalbard (Hornsund and Pyramiden) were collected during the June/July 2019 field campaign and examined in the laboratory. Despite the differences in their climate and topography, both locations are characterised by very similar spatial patterns of the deposition. On the one hand, strong linear negative relationship between the altitude of the sample taken and its concentration was found in low altitude (below 300 m a.s.l.), suggesting a strong influence of local HLD sources. On the other hand, almost constant concentrations were found at higher elevated sampling sites (above 300 m a.s.l.). This suggests a predominantly long-range transport in high altitude areas. The importance of local sources in the lower altitude corresponds well with the generally higher concentrations of HLD in the Pyramiden area. This region has a drier, continental climate and more deglaciated bare land surfaces, which favour more sediment to be uplifted in comparison with the more maritime climate of Hornsund area in the southern part of Svalbard. The spatial division between the local and long-range transport is supported by the proportion of certain lithophile elements in the altitude gradient. Full article

(This article belongs to the Special Issue Long-Range Transport of Dust over the High-Latitude Regions)

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21 pages, 8049 KiB

Open AccessEditor’s ChoiceArticle

Smart Climate Hydropower Tool: A Machine-Learning Seasonal Forecasting Climate Service to Support Cost–Benefit Analysis of Reservoir Management

by Arthur H. Essenfelder, Francesca Larosa, Paolo Mazzoli, Stefano Bagli, Davide Broccoli, Valerio Luzzi, Jaroslav Mysiak, Paola Mercogliano and Francesco dalla Valle

Atmosphere 2020, 11(12), 1305; https://doi.org/10.3390/atmos11121305 - 1 Dec 2020

Cited by 15 | Viewed by 4046

Abstract

This study proposes a climate service named Smart Climate Hydropower Tool (SCHT) and designed as a hybrid forecast system for supporting decision-making in a context of hydropower production. SCHT is technically designed to make use of information from state-of-art seasonal forecasts provided by [...] Read more.

This study proposes a climate service named Smart Climate Hydropower Tool (SCHT) and designed as a hybrid forecast system for supporting decision-making in a context of hydropower production. SCHT is technically designed to make use of information from state-of-art seasonal forecasts provided by the Copernicus Climate Data Store (CDS) combined with a range of different machine learning algorithms to perform the seasonal forecast of the accumulated inflow discharges to the reservoir of hydropower plants. The machine learning algorithms considered include support vector regression, Gaussian processes, long short-term memory, non-linear autoregressive neural networks with exogenous inputs, and a deep-learning neural networks model. Each machine learning model is trained over past decades datasets of recorded data, and forecast performances are validated and evaluated using separate test sets with reference to the historical average of discharge values and simpler multiparametric regressions. Final results are presented to the users through a user-friendly web interface developed from a tied connection with end-users in an effective co-design process. Methods are tested for forecasting the accumulated seasonal river discharges up to six months in advance for two catchments in Colombia, South America. Results indicate that the machine learning algorithms that make use of a complex and/or recurrent architecture can better simulate the temporal dynamic behaviour of the accumulated river discharge inflow to both case study reservoirs, thus rendering SCHT a useful tool in providing information for water resource managers in better planning the allocation of water resources for different users and for hydropower plant managers when negotiating power purchase contracts in competitive energy markets. Full article

(This article belongs to the Special Issue Artificial Intelligence and Machine Learning: Application in Predictive Hydrological Models)

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17 pages, 4437 KiB

Open AccessEditor’s ChoiceArticle

Future Crop Yield Projections Using a Multi-model Set of Regional Climate Models and a Plausible Adaptation Practice in the Southeast United States

by D. W. Shin, Steven Cocke, Guillermo A. Baigorria, Consuelo C. Romero, Baek-Min Kim and Ki-Young Kim

Atmosphere 2020, 11(12), 1300; https://doi.org/10.3390/atmos11121300 - 30 Nov 2020

Cited by 5 | Viewed by 2667

Abstract

Since maize, peanut, and cotton are economically valuable crops in the southeast United States, their yield amount changes in a future climate are attention-grabbing statistics demanded by associated stakeholders and policymakers. The Crop System Modeling—Decision Support System for Agrotechnology Transfer (CSM-DSSAT) models of [...] Read more.

Since maize, peanut, and cotton are economically valuable crops in the southeast United States, their yield amount changes in a future climate are attention-grabbing statistics demanded by associated stakeholders and policymakers. The Crop System Modeling—Decision Support System for Agrotechnology Transfer (CSM-DSSAT) models of maize, peanut, and cotton are, respectively, driven by the North American Regional Climate Change Assessment Program (NARCCAP) Phase II regional climate models to estimate current (1971–2000) and future (2041–2070) crop yield amounts. In particular, the future weather/climate data are based on the Special Report on Emission Scenarios (SRES) A2 emissions scenario. The NARCCAP realizations show on average that there will be large temperature increases (~2.7 °C) and minor rainfall decreases (~−0.10 mm/day) with pattern shifts in the southeast United States. With these future climate projections, the overall future crop yield amounts appear to be reduced under rainfed conditions. A better estimate of future crop yield amounts might be achievable by utilizing the so-called weighted ensemble method. It is proposed that the reduced crop yield amounts in the future could be mitigated by altering the currently adopted local planting dates without any irrigation support. Full article

(This article belongs to the Special Issue Advances in Improving Crop Adaptation in a Changing Climate)

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23 pages, 16302 KiB

Open AccessEditor’s ChoiceArticle

Monitoring Dust Events Using Doppler Lidar and Ceilometer in Iceland

by Shu Yang, Jana Preißler, Matthias Wiegner, Sibylle von Löwis, Guðrún Nína Petersen, Michelle Maree Parks and David Christian Finger

Atmosphere 2020, 11(12), 1294; https://doi.org/10.3390/atmos11121294 - 30 Nov 2020

Cited by 17 | Viewed by 4106

Abstract

Ground-based lidars and ceilometers are widely used for dust and volcanic ash observation around the world. This is particularly interesting in Iceland where high-altitude dust events occur frequently during strong wind conditions and volcanic eruptions. To explore the possible application of such technologies [...] Read more.

Ground-based lidars and ceilometers are widely used for dust and volcanic ash observation around the world. This is particularly interesting in Iceland where high-altitude dust events occur frequently during strong wind conditions and volcanic eruptions. To explore the possible application of such technologies in Iceland for monitoring dust events, we used a combination of Doppler wind lidars with depolarization channels, ceilometers, and other instruments, to monitor two dust events that occurred in Iceland during summer 2019. We applied a verified ceilometer data processing procedure with customized local corrections and developed a new procedure to process Doppler lidar data for aerosols measurements. Both lidar and ceilometer observations can be used to detect the dust layer and reveal the temporal and vertical distribution of dust aerosols in Iceland. The depolarization ratio measurements indicate that the weather conditions, e.g., relative humidity, could have a significant impact on lidar measurements. We conclude that using Doppler wind lidar and ceilometer measurements to monitor volcanic and sedimentary aerosols is possible and may be used to provide important information to the scientific community. Full article

(This article belongs to the Special Issue Lidar Remote Sensing Techniques for Atmospheric Aerosols)

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17 pages, 9084 KiB

Open AccessEditor’s ChoiceArticle

Association between the Concentration and the Elemental Composition of Outdoor PM_2.5 and Respiratory Diseases in Schoolchildren: A Multicenter Study in the Mediterranean Area

by Christopher Zammit, David Bilocca, Silvia Ruggieri, Gaspare Drago, Cinzia Perrino, Silvia Canepari, Martin Balzan, Stephen Montefort, Giovanni Viegi, Fabio Cibella and on behalf of the RESPIRA Collaborative Project Group

Atmosphere 2020, 11(12), 1290; https://doi.org/10.3390/atmos11121290 - 29 Nov 2020

Cited by 7 | Viewed by 2637

Abstract

Abstract: Exposure to outdoor air pollution has been shown to increase asthma symptoms. We assessed the potential role of particulate matter with aerodynamic diameter <2.5 μm (PM_2.5) on respiratory condition in schoolchildren in the south Mediterranean area. A total of [...] Read more.

Abstract: Exposure to outdoor air pollution has been shown to increase asthma symptoms. We assessed the potential role of particulate matter with aerodynamic diameter <2.5 μm (PM_2.5) on respiratory condition in schoolchildren in the south Mediterranean area. A total of 2400 children aged 11–14 years were recruited, and data on their symptoms were collected through an ISAAC (International Study of Asthma and Allergies in Childhood)-based questionnaire. Outdoor PM_2.5 was collected for 48 consecutive hours in the schoolyards of their schools and selected residential outdoor areas. The levels of PM_2.5 were measured, along with its elemental composition. The incidence of an acute respiratory illness within the first 2 years of life was higher amongst Sicilian children when compared to Maltese children (29.7% vs. 13.5% respectively, p < 0.0001). Malta had a significantly higher prevalence of doctor‐diagnosed asthma, when compared to Sicily (18.0% Malta vs. 7.5% Sicily, p <0.0001). Similarly, current asthma (7.8% vs. 2.9%, p < 0.0001) and use of asthma medication in the last 12 months (12.1% vs. 4.9%, p < 0.0001) were more frequent amongst Maltese children. Total median PM_2.5 was 12.9 μg/m³ in Sicily and 17.9 μg/m³ in Malta. PM_2.5 levels were highest in the Maltese urban town of Hamrun (23.6 μg/m³), while lowest in the rural Sicilian town of Niscemi (10.9 μg/m³, p < 0.0001). Hamrun also exhibited the highest levels of nickel, vanadium, lead, zinc, antimony, and manganese, whilst the Sicilian city of Gela had the highest levels of cadmium, and the highest level of PM_2.5 when compared to rural Sicily. Elevated levels of PM_2.5 were positively associated with the prevalence of doctor diagnosed asthma (odds ratio (OR) 1.05), current asthma (OR 1.06), and use of asthma medication (OR 1.06). All elements in PM_2.5 showed increased OR for doctor diagnosed asthma, while higher concentrations of Cd and Mn were associated with higher prevalence of rhinitis. Full article

(This article belongs to the Special Issue Air Quality and Health in the Mediterranean)

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18 pages, 1449 KiB

Open AccessEditor’s ChoiceCommunication

A Note on the Assessment of the Effect of Atmospheric Factors and Components on Humans

by Andreas Matzarakis

Atmosphere 2020, 11(12), 1283; https://doi.org/10.3390/atmos11121283 - 28 Nov 2020

Cited by 14 | Viewed by 2540

Abstract

The aim of this contribution is both to demonstrate and to explore the general assessment pertaining to the effects of atmospheric factors on human health and general wellbeing. While humans are aware of such effects, particularly individually, their concrete and synergetic effects with [...] Read more.

The aim of this contribution is both to demonstrate and to explore the general assessment pertaining to the effects of atmospheric factors on human health and general wellbeing. While humans are aware of such effects, particularly individually, their concrete and synergetic effects with the human physiological system are, comparatively, not well comprehended. In human biometeorological studies and approaches, the aforementioned effects are analyzed in terms of their effect pathways, and the development of single or complex approaches. Recurrently in the existing literature, such approaches are mostly defined and, respectively, targeted as indexes. The evaluation and assessment of similar factors and parameters that present related effects were subsequently put together and quantified. This approach is described as ‘effective complexes’ or components. The most well-known examples are the thermal complex, air pollution complex (which can be divided into the biological (pollen) and anthropogenic (air pollutants) factors), actinic complex, and finally, the recent or rapid weather changes complex. Most of the approaches focus on the negative effects consequential to the established criteria ranging from empirical outputs, to epidemiological studies. As a result, the presented approach does not only include the negative effects or implications on humans. Instead, it also highlights the neutral and positive effects which were acknowledged by the research. The approach deals furthermore with the combined effects of different complexes or components and incorporates different weightings of the factors based on the disclosed effects. In addition, seasonal and exposure factors are deliberated upon to differentiate annual variability factors. Finally, the presented approach builds upon a way in which to cogitate how the complex interactions associated to weather and climate can be quantified in a more appropriate way in the context of human health. The approach aims to be applied for a specific weather forecast enabling the communication and balance between human health factors, and also more encompassing climatic analysis. Full article

(This article belongs to the Special Issue Review Special Issue: Human Biometeorology—Link to Climate Impact Research)

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15 pages, 8154 KiB

Open AccessEditor’s ChoiceArticle

Spatial and Temporal Exposure Assessment to PM_2.5 in a Community Using Sensor-Based Air Monitoring Instruments and Dynamic Population Distributions

by Jinhyeon Park, Wondeuk Jo, Mansu Cho, Jeongil Lee, Hunjoo Lee, SungChul Seo, Chulmin Lee and Wonho Yang

Atmosphere 2020, 11(12), 1284; https://doi.org/10.3390/atmos11121284 - 28 Nov 2020

Cited by 10 | Viewed by 3839

Abstract

This research was to conduct a pilot study for two consecutive days in order to assess fine particulate matter (PM_2.5) exposure of an entire population in a community. We aimed to construct a surveillance system by analyzing the observed spatio-temporal variation [...] Read more.

This research was to conduct a pilot study for two consecutive days in order to assess fine particulate matter (PM_2.5) exposure of an entire population in a community. We aimed to construct a surveillance system by analyzing the observed spatio-temporal variation of exposure. Guro-gu in Seoul, South Korea, was divided into 2,204 scale grids of 100 m each. Hourly exposure concentrations of PM_2.5 were modeled by the inverse distance weighted method, using 24 sensor-based air monitoring instruments and the indoor-to-outdoor concentration ratio. Population distribution was assessed using mobile phone network data and indoor residential rates, according to sex and age over time. Exposure concentration, population distribution, and population exposure were visualized to present spatio-temporal variation. The PM_2.5 exposure of the entire population of Guro-gu was calculated by population-weighted average exposure concentration. The average concentration of outdoor PM_2.5 was 42.1 µg/m³, which was lower than the value of the beta attenuation monitor measured by fixed monitoring station. Indoor concentration was estimated using an indoor-to-outdoor PM_2.5 concentration ratio of 0.747. The population-weighted average exposure concentration of PM_2.5 was 32.4 µg/m³. Thirty-one percent of the population exceeded the Korean Atmospheric Environmental Standard for PM_2.5 over a 24 h average period. The results of this study can be used in a long-term aggregate and cumulative PM_2.5 exposure assessment, and as a basis for policy decisions on public health management among policymakers and stakeholders. Full article

(This article belongs to the Special Issue Challenges in Measuring and Assessing Environmental Health)

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19 pages, 6881 KiB

Open AccessEditor’s ChoiceArticle

Impact of Meteorological Changes on Particulate Matter and Aerosol Optical Depth in Seoul during the Months of June over Recent Decades

by Seohee H. Yang, Jaein I. Jeong, Rokjin J. Park and Minjoong J. Kim

Atmosphere 2020, 11(12), 1282; https://doi.org/10.3390/atmos11121282 - 27 Nov 2020

Cited by 11 | Viewed by 3104

Abstract

The effects of meteorological changes on particulate matter with a diameter of 10 microns or less (PM₁₀, referred to as PM in this study) and aerosol optical depth (AOD) in Seoul were investigated using observational and modeling analysis. AOD satellite data [...] Read more.

The effects of meteorological changes on particulate matter with a diameter of 10 microns or less (PM₁₀, referred to as PM in this study) and aerosol optical depth (AOD) in Seoul were investigated using observational and modeling analysis. AOD satellite data were used, obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS), and PM concentration data were used from in-situ observations. The Modern-Era Retrospective Analysis for Research and Applications (MERRA) and MERRA Version 2 (MERRA-2) were used for meteorological field analysis in modeling and observation data. The results from this investigation show that meteorological effects on PM and AOD were strong in the month of June, revealing a clear decreasing trend in recent decades. The investigation focused on the underlying mechanisms influencing the reduction in PM resulting from meteorological changes during the months of June. The results of this study reveal that decreases in atmospheric stability and humidity induced the aerosol change observed in recent decades. The changes in atmospheric stability and humidity are highly correlated with changes in the intensity of the East Asian summer monsoon (EASM). This suggests that the unstable and drying atmosphere by weakening of the EASM in recent decades has improved PM air quality in Seoul during the summer. The effects of atmospheric stability and humidity were also observed to vary depending on the aerosol species. Humidity only affects hydrophilic aerosols such as sulfate, nitrate, and ammonium, whereas atmospheric stability affects all species of aerosols, including carbonaceous aerosols. Full article

(This article belongs to the Special Issue Aerosol-Climate Interaction)

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19 pages, 3820 KiB

Open AccessEditor’s ChoiceArticle

Representation of the 2016 Korean Heatwave in the Unified Model Global NWP Forecasts: The Impact of Remotely Forced Model Errors and Atmosphere-Ocean Coupling

by Eun-Jung Kim, Charline Marzin, Sean F. Milton, Kyung-On Boo, Yoonjae Kim, Jiyoung Oh and Hyun-Suk Kang

Atmosphere 2020, 11(12), 1275; https://doi.org/10.3390/atmos11121275 - 25 Nov 2020

Cited by 3 | Viewed by 2223

Abstract

This study investigates the effects of atmosphere-ocean coupling for medium-range forecasts by using coupled numerical weather prediction (NWP) experiments based on the unified model (UM) on a case study of the 2016 heatwave over the Korean Peninsula. Atmospheric nudging experiments were carried out [...] Read more.

This study investigates the effects of atmosphere-ocean coupling for medium-range forecasts by using coupled numerical weather prediction (NWP) experiments based on the unified model (UM) on a case study of the 2016 heatwave over the Korean Peninsula. Atmospheric nudging experiments were carried out to determine the key regions which may have large impacts on the forecasts of the heat wave. The results of the nudging experiments suggest that key forcing from the Mongolia region gives the largest impact to this case by causing a transport of warm air from the northwest part of Korea. Moreover, the Pacific region shows an important role in the global circulation in nudging experiments. Results from the atmosphere-ocean coupled model show no clear benefit for the extreme heat wave temperatures in this case. In addition, more model development seems to be needed to improve the representation of sea surface temperature (SST) in some key areas. Nevertheless, it is confirmed that the atmosphere-ocean coupled simulation produces a better representation of aspects of the large-scale flow such as the blocking high over the Kamchatka Peninsula, the high pressure system in the northwest Pacific and Hadley circulation. The results presented in this study show that atmosphere-ocean coupling can be an important way to improve the deterministic model forecasts as the lead time increases beyond a few days. Full article

(This article belongs to the Special Issue Meteorological Extremes in Korea: Prediction, Assessment, and Impact)

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13 pages, 8980 KiB

Open AccessEditor’s ChoiceArticle

A Hot Blob Eastward of New Zealand in December 2019

by Jian Shi, Ziyan Chen, Saisai Ding and Yiqun Lu

Atmosphere 2020, 11(12), 1267; https://doi.org/10.3390/atmos11121267 - 24 Nov 2020

Cited by 2 | Viewed by 2600

Abstract

A hot blob for near-surface water was identified eastward of New Zealand in the South Pacific in December 2019, which was the second strongest event on record in this region. Its sea surface temperature anomalies reached up to 5 °C, and the anomalous [...] Read more.

A hot blob for near-surface water was identified eastward of New Zealand in the South Pacific in December 2019, which was the second strongest event on record in this region. Its sea surface temperature anomalies reached up to 5 °C, and the anomalous warming penetrated around 40 m deep vertically. From the atmospheric perspective, the anomalous high-pressure system from the surface up to 300 hPa lasted for about 50 days, accompanied by the blocking pattern at 500 hPa and a deep warming air column extending downward to the surface. A mixed-layer heat budget analysis revealed that the surface heat flux term was the primary factor contributing to the development of this hot blob, with more shortwave radiation due to the persistent high-pressure system and lack of clouds as well as higher temperature of the troposphere aloft denoted by sensible heat. The oceanic contribution including the horizontal advection and vertical entrainment was changeable and accounted for less than 50%. Moreover, we used the strongest hot blob event which peaked in December 2001 as another example to evaluate the robustness of results derived from the 2019 case. The results show similar circulation features and driving factors, which indicate the robustness of the above characteristics. Full article

(This article belongs to the Special Issue Temperature Extremes and Atmospheric Circulation)

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25 pages, 3470 KiB

Open AccessEditor’s ChoiceArticle

New Record of Dust Input and Provenance During Glacial Periods in Western Australia Shelf (IODP Expedition 356, Site U1461) from the Middle to Late Pleistocene

by Margot Courtillat, Maximilian Hallenberger, Maria-Angela Bassetti, Dominique Aubert, Catherine Jeandel, Lars Reuning, Chelsea Korpanty, Pierre Moissette, Stéphanie Mounic and Mariem Saavedra-Pellitero

Atmosphere 2020, 11(11), 1251; https://doi.org/10.3390/atmos11111251 - 20 Nov 2020

Cited by 10 | Viewed by 4637

Abstract

International Ocean Discovery Program (IODP) Expedition 356 Site U1461 represents one of the few records from the North West Australian shelf that provides information about aridity fluctuations in Australia during the Quaternary. A combination of chronostratigraphic indicators revealed the (partial) preservation of two [...] Read more.

International Ocean Discovery Program (IODP) Expedition 356 Site U1461 represents one of the few records from the North West Australian shelf that provides information about aridity fluctuations in Australia during the Quaternary. A combination of chronostratigraphic indicators revealed the (partial) preservation of two major glaciations (Marine Isotope Stage (MIS) 2 and MIS 12) in the sedimentary record. The faunal content (mainly benthic foraminifera, corals and bryozoans) was analyzed to estimate paleo-environments and paleo-depths in order to determine if these sediments have been remobilized by reworking processes. Despite the occurrence of a depositional hiatus (including MIS 5d to MIS 9-time interval), the excellent preservation of faunal content suggests that the preserved sediment is in situ. The geochemical composition of the sediments (Nd and major elements) indicates that during MIS 12 riverine input was likely reduced because of enhanced aridity, and the sediment provenance (mainly atmospheric dust) is likely in the central (Lake Eyre) or eastern (Murray Darling Basin) parts of the Australian continent. MIS 2 is confirmed to be one of the driest periods recorded in Australia but with mixed dust sources from the eastern and western parts of the continent. More humid conditions followed the glacial maximum, which might correspond to the peak of the Indian-Australian Summer Monsoon. Full article

(This article belongs to the Special Issue Paleoclimate and Its Connection with Future Climate Change)

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18 pages, 3726 KiB

Open AccessEditor’s ChoiceArticle

Regional Distribution of Net Radiation over Different Ecohydrological Land Surfaces

by Md Masudur Rahman, Wanchang Zhang and Arfan Arshad

Atmosphere 2020, 11(11), 1229; https://doi.org/10.3390/atmos11111229 - 14 Nov 2020

Cited by 4 | Viewed by 3444

Abstract

Net radiation is an important component of the earth’s surface energy balance, which plays a vital role in the evolution of regional climate or climate change. The estimation of this component at regional or global scales is critical and challenging due to the [...] Read more.

Net radiation is an important component of the earth’s surface energy balance, which plays a vital role in the evolution of regional climate or climate change. The estimation of this component at regional or global scales is critical and challenging due to the sparse and limited ground-based observations. This paper made an attempt to analyze the feasibility of a remote sensing-based surface energy balance model using satellite (TERRA/MODIS) data to derive the net radiation (R_n). In the present study, MODIS data at 15 different days of the year (DOY) were utilized to visualize the spatial pattern of net radiation flux over three versatile and heterogeneous ecohydrological land surfaces (upstream, midstream, and downstream) of northwest China (Heihe river basin). The results revealed that the estimated net radiation from the satellite data agrees well with the ground-based measurements over three different surfaces, with a mean relative error of 9.33% over the upstream superstation (grasslands), 13.95% over the middle stream superstation (croplands), and 11.63% over the downstream superstation (mixed forests), where the overall relative error was 11.64% with an overall rmse of 29.36 W/m² in the study area. The regional distribution of net radiation over the versatile land surfaces was validated well at a large scale during the five-month period and over different land surfaces. It was also observed that the spatial pattern of net radiation varies spatially over three different landscape regions during four different days of the year, which might be associated with different climatic conditions and landscape features in these regions. The overall findings of this study concluded that satellite-derived net radiation can rationally be obtained using a single-source remote sensing model over different land surfaces. Full article

(This article belongs to the Special Issue Radiative Transfer in the Earth Atmosphere)

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21 pages, 4508 KiB

Open AccessEditor’s ChoiceArticle

Variability of Chemical Properties of the Atmospheric Aerosol above Lake Baikal during Large Wildfires in Siberia

by Liudmila Golobokova, Tamara Khodzher, Olga Khuriganova, Irina Marinayte, Natalia Onishchuk, Polina Rusanova and Vladimir Potemkin

Atmosphere 2020, 11(11), 1230; https://doi.org/10.3390/atmos11111230 - 14 Nov 2020

Cited by 22 | Viewed by 3088

Abstract

The article analyzes the chemical composition (ions, elements, and polycyclic aromatic hydrocarbons) of the atmospheric aerosol in the near-water layer of the atmosphere above Lake Baikal during wildfires in Siberia. Aerosol deposition affects the aquatic environment of the watershed basin and the lake [...] Read more.

The article analyzes the chemical composition (ions, elements, and polycyclic aromatic hydrocarbons) of the atmospheric aerosol in the near-water layer of the atmosphere above Lake Baikal during wildfires in Siberia. Aerosol deposition affects the aquatic environment of the watershed basin and the lake itself. The current law on Lake Baikal limits the activity of the permanent stationary anthropogenic sources of the aerosol in the central ecological zone, and they do not have a significant negative impact. Wildfires can have a much greater impact on the environment. Smoke emissions entering the area of Lake Baikal due to wildfires change the chemical properties of the atmospheric aerosol and increase its mass and number concentration. The concentrations of NH₄⁺, K⁺, NO₃⁻, and SO₄²⁻, which enter with submicron aerosol fraction, increase in the ionic composition of the aerosol. The composition of polyaromatic compounds changes, and their concentrations increase. Elevated concentrations of B, Mn, Zn, As, Sr, Cd, and Pb in the composition of aerosol indicate the influx of air masses from the areas prone to wildfires. Despite the sporadic effects of these natural factors, they affect the pollution of various Baikal ecosystems, especially small tributaries of the lake, whose main supply is atmospheric. Full article

(This article belongs to the Special Issue Air Pollution Estimation)

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25 pages, 5997 KiB

Open AccessEditor’s ChoiceArticle

Source Apportionment of Aerosol at a Coastal Site and Relationships with Precipitation Chemistry: A Case Study over the Southeast United States

by Andrea F. Corral, Hossein Dadashazar, Connor Stahl, Eva-Lou Edwards, Paquita Zuidema and Armin Sorooshian

Atmosphere 2020, 11(11), 1212; https://doi.org/10.3390/atmos11111212 - 10 Nov 2020

Cited by 17 | Viewed by 4286

Abstract

This study focuses on the long-term aerosol and precipitation chemistry measurements from colocated monitoring sites in Southern Florida between 2013 and 2018. A positive matrix factorization (PMF) model identified six potential emission sources impacting the study area. The PMF model solution yielded the [...] Read more.

This study focuses on the long-term aerosol and precipitation chemistry measurements from colocated monitoring sites in Southern Florida between 2013 and 2018. A positive matrix factorization (PMF) model identified six potential emission sources impacting the study area. The PMF model solution yielded the following source concentration profiles: (i) combustion; (ii) fresh sea salt; (iii) aged sea salt; (iv) secondary sulfate; (v) shipping emissions; and (vi) dust. Based on these results, concentration-weighted trajectory maps were developed to identify sources contributing to the PMF factors. Monthly mean precipitation pH values ranged from 4.98 to 5.58, being positively related to crustal species and negatively related to SO₄²⁻. Sea salt dominated wet deposition volume-weighted concentrations year-round without much variability in its mass fraction in contrast to stronger seasonal changes in PM_2.5 composition where fresh sea salt was far less influential. The highest mean annual deposition fluxes were attributed to Cl⁻, NO₃⁻, SO₄²⁻, and Na⁺ between April and October. Nitrate is strongly correlated with dust constituents (unlike sea salt) in precipitation samples, indicative of efficient partitioning to dust. Interrelationships between precipitation chemistry and aerosol species based on long-term surface data provide insight into aerosol–cloud–precipitation interactions. Full article

(This article belongs to the Special Issue Feature Papers of Aerosol Impacts on Climate and Air Quality)

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18 pages, 6294 KiB

Open AccessEditor’s ChoiceArticle

Assessing Suitable Areas of Common Grapevine (Vitis vinifera L.) for Current and Future Climate Situations: The CDS Toolbox SDM

by Guillermo Hinojos Mendoza, Cesar Arturo Gutierrez Ramos, Dulce María Heredia Corral, Ricardo Soto Cruz and Emmanuel Garbolino

Atmosphere 2020, 11(11), 1201; https://doi.org/10.3390/atmos11111201 - 6 Nov 2020

Cited by 4 | Viewed by 2873

Abstract

Climate Data Science (CDS) Toolbox Species Distribution Model (SDM) aims identifying the suitable areas for species, community of species and landscape units. This model is based on the use of 23 variables available over the Internet, for which any assumptions are formulated about [...] Read more.

Climate Data Science (CDS) Toolbox Species Distribution Model (SDM) aims identifying the suitable areas for species, community of species and landscape units. This model is based on the use of 23 variables available over the Internet, for which any assumptions are formulated about their relationships with the spatial distribution of species. The application of CDS Toolbox SDM on the assessment of the potential impact of two scenarios of climate change (Representative Concentration Pathways RCP4.5 and RCP6.0) on the suitability of grapevine crops in France shows a general decrease of the most suitable areas for grapevine crops between 41% and 83% towards 2070 according to the current location of the vineyard parcels. The results underline a potential shift of the suitable areas in northern part of the French territory. They also show a potential shift of the most suitable areas in altitude (60 m in average) for RCP6.0 scenario. Finally, the model shows that RCP4.5 scenario should be more drastic than RCP6.0 scenario by 2050 and 2070. In effect, the model underlines a significant potential decrease of cultivated crops in the areas of high probably of suitable areas, according to the baseline scenario. This decrease would be of 630,000 ha for 2070 RCP4.5 scenario and 330,000 ha for 2070 RCP6.0 scenario. Full article

(This article belongs to the Special Issue Plant Adaptation to Global Climate Change)

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18 pages, 2223 KiB

Open AccessEditor’s ChoiceArticle

Impact of the COVID-19 Pandemic Lockdown on Air Pollution in 20 Major Cities around the World

by Franck Fu, Kathleen L. Purvis-Roberts and Branwen Williams

Atmosphere 2020, 11(11), 1189; https://doi.org/10.3390/atmos11111189 - 3 Nov 2020

Cited by 100 | Viewed by 12123

Abstract

In order to fight against the spread of COVID-19, the most hard-hit countries in the spring of 2020 implemented different lockdown strategies. To assess the impact of the COVID-19 pandemic lockdown on air quality worldwide, Air Quality Index (AQI) data was used to [...] Read more.

In order to fight against the spread of COVID-19, the most hard-hit countries in the spring of 2020 implemented different lockdown strategies. To assess the impact of the COVID-19 pandemic lockdown on air quality worldwide, Air Quality Index (AQI) data was used to estimate the change in air quality in 20 major cities on six continents. Our results show significant declines of AQI in NO₂, SO₂, CO, PM_2.5 and PM₁₀ in most cities, mainly due to the reduction of transportation, industry and commercial activities during lockdown. This work shows the reduction of primary pollutants, especially NO₂, is mainly due to lockdown policies. However, preexisting local environmental policy regulations also contributed to declining NO₂, SO₂ and PM_2.5 emissions, especially in Asian countries. In addition, higher rainfall during the lockdown period could cause decline of PM_2.5, especially in Johannesburg. By contrast, the changes of AQI in ground-level O₃ were not significant in most of cities, as meteorological variability and ratio of VOC/NO_x are key factors in ground-level O₃ formation. Full article

(This article belongs to the Section Air Quality)

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21 pages, 2613 KiB

Open AccessEditor’s ChoiceArticle

Integrating in situ Measurements and City Scale Modelling to Assess the COVID–19 Lockdown Effects on Emissions and Air Quality in Athens, Greece

by Georgios Grivas, Eleni Athanasopoulou, Anastasia Kakouri, Jennifer Bailey, Eleni Liakakou, Iasonas Stavroulas, Panayiotis Kalkavouras, Aikaterini Bougiatioti, Dimitris G. Kaskaoutis, Michel Ramonet, Nikolaos Mihalopoulos and Evangelos Gerasopoulos

Atmosphere 2020, 11(11), 1174; https://doi.org/10.3390/atmos11111174 - 30 Oct 2020

Cited by 49 | Viewed by 6557

Abstract

The lockdown measures implemented worldwide to slow the spread of the COVID–19 pandemic have allowed for a unique real-world experiment, regarding the impacts of drastic emission cutbacks on urban air quality. In this study we assess the effects of a 7-week (23 March–10 [...] Read more.

The lockdown measures implemented worldwide to slow the spread of the COVID–19 pandemic have allowed for a unique real-world experiment, regarding the impacts of drastic emission cutbacks on urban air quality. In this study we assess the effects of a 7-week (23 March–10 May 2020) lockdown in the Greater Area of Athens, coupling in situ observations with estimations from a meteorology-atmospheric chemistry model. Measurements in central Athens during the lockdown were compared with levels during the pre- and post-lockdown 3-week periods and with respective levels in the four previous years. We examined regulatory pollutants as well as CO₂, black carbon (BC) and source-specific BC components. Models were run for pre-lockdown and lockdown periods, under baseline and reduced-emissions scenarios. The in-situ results indicate mean concentration reductions of 30–35% for traffic-related pollutants in Athens (NO₂, CO, BC from fossil fuel combustion), compared to the pre-lockdown period. A large reduction (53%) was observed also for the urban CO₂ enhancement while the reduction for PM_2.5 was subtler (18%). Significant reductions were also observed when comparing the 2020 lockdown period with past years. However, levels rebounded immediately following the lift of the general lockdown. The decrease in measured NO₂ concentrations was reproduced by the implementation of the city scale model, under a realistic reduced-emissions scenario for the lockdown period, anchored at a 46% decline of road transport activity. The model permitted the assessment of air quality improvements on a spatial scale, indicating that NO₂ mean concentration reductions in areas of the Athens basin reached up to 50%. The findings suggest a potential for local traffic management strategies to reduce ambient exposure and to minimize exceedances of air quality standards for primary pollutants. Full article

(This article belongs to the Special Issue Coronavirus Pandemic Shutdown Effects on Urban Air Quality)

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22 pages, 5117 KiB

Open AccessEditor’s ChoiceArticle

Spatial Distribution of Atmospheric Aerosol Physicochemical Characteristics in the Russian Sector of the Arctic Ocean

by Sergey M. Sakerin, Dmitry M. Kabanov, Valery I. Makarov, Viktor V. Pol’kin, Svetlana A. Popova, Olga V. Chankina, Anton O. Pochufarov, Vladimir F. Radionov and Denis D. Rize

Atmosphere 2020, 11(11), 1170; https://doi.org/10.3390/atmos11111170 - 29 Oct 2020

Cited by 20 | Viewed by 2576

Abstract

The results from studies of aerosol in the Arctic atmosphere are presented: the aerosol optical depth (AOD), the concentrations of aerosol and black carbon, as well as the chemical composition of the aerosol. The average aerosol characteristics, measured during nine expeditions (2007–2018) in [...] Read more.

The results from studies of aerosol in the Arctic atmosphere are presented: the aerosol optical depth (AOD), the concentrations of aerosol and black carbon, as well as the chemical composition of the aerosol. The average aerosol characteristics, measured during nine expeditions (2007–2018) in the Eurasian sector of the Arctic Ocean, had been 0.068 for AOD (0.5 µm); 2.95 cm⁻³ for particle number concentrations; 32.1 ng/m³ for black carbon mass concentrations. Approximately two–fold decrease of the average characteristics in the eastern direction (from the Barents Sea to Chukchi Sea) is revealed in aerosol spatial distribution. The average aerosol characteristics over the Barents Sea decrease in the northern direction: black carbon concentrations by a factor of 1.5; particle concentrations by a factor of 3.7. These features of the spatial distribution are caused mainly by changes in the content of fine aerosol, namely: by outflows of smokes from forest fires and anthropogenic aerosol. We considered separately the measurements of aerosol characteristics during two expeditions in 2019: in the north of the Barents Sea (April) and along the Northern Sea Route (July–September). In the second expedition the average aerosol characteristics turned out to be larger than multiyear values: AOD reached 0.36, particle concentration up to 8.6 cm⁻³, and black carbon concentration up to 179 ng/m³. The increased aerosol content was affected by frequent outflows of smoke from forest fires. The main (99%) contribution to the elemental composition of aerosol in the study regions was due to Ca, K, Fe, Zn, Br, Ni, Cu, Mn, and Sr. The spatial distribution of the chemical composition of aerosols was analogous to that of microphysical characteristics. The lowest concentrations of organic and elemental carbon (OC, EC) and of most elements are observed in April in the north of the Barents Sea, and the maximal concentrations in Far East seas and in the south of the Barents Sea. The average contents of carbon in aerosol over seas of the Asian sector of the Arctic Ocean are OC = 629 ng/m³, EC = 47 ng/m³. Full article

(This article belongs to the Special Issue Air Pollution Estimation)

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19 pages, 7599 KiB

Open AccessEditor’s ChoiceArticle

Assessment and Correction of Solar Radiation Measurements with Simple Neural Networks

by Jason Kelley

Atmosphere 2020, 11(11), 1160; https://doi.org/10.3390/atmos11111160 - 27 Oct 2020

Cited by 1 | Viewed by 2437

Abstract

Solar radiation received at the Earth’s surface provides the energy driving all micro-meteorological phenomena. Local solar radiation measurements are used to estimate energy mediated processes such as evapotranspiration (ET); this information is important in managing natural resources. However, the technical requirements to reliably [...] Read more.

Solar radiation received at the Earth’s surface provides the energy driving all micro-meteorological phenomena. Local solar radiation measurements are used to estimate energy mediated processes such as evapotranspiration (ET); this information is important in managing natural resources. However, the technical requirements to reliably measure solar radiation limits more extensive adoption of data-driven management. High-quality radiation sensors are expensive, delicate, and require skill to maintain. In contrast, low-cost sensors are widely available, but may lack long-term reliability and intra-sensor repeatability. As weather stations measure solar radiation and other parameters simultaneously, machine learning can be used to integrate various types of environmental data, identify periods of erroneous measurements, and estimate corrected values. We demonstrate two case studies in which we use neural networks (NN) to augment direct radiation measurements with data from co-located sensors, and generate radiation estimates with comparable accuracy to the data typically available from agro-meteorology networks. NN models that incorporated radiometer data reproduced measured radiation with an R² of 0.9–0.98, and RMSE less than 100 Wm⁻², while models using only weather parameters obtained R² less than 0.75 and RMSE greater than 140 Wm⁻². These cases show that a simple NN implementation can complement standard procedures for estimating solar radiation, create opportunities to measure radiation at low-cost, and foster adoption of data-driven management. Full article

(This article belongs to the Special Issue Machine Learning for Solar Radiation Estimation)

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17 pages, 5307 KiB

Open AccessEditor’s ChoiceArticle

Prediction of Short-Time Cloud Motion Using a Deep-Learning Model

by Xinyue Su, Tiejian Li, Chenge An and Guangqian Wang

Atmosphere 2020, 11(11), 1151; https://doi.org/10.3390/atmos11111151 - 26 Oct 2020

Cited by 11 | Viewed by 6252

Abstract

A cloud image can provide significant information, such as precipitation and solar irradiation. Predicting short-time cloud motion from images is the primary means of making intra-hour irradiation forecasts for solar-energy production and is also important for precipitation forecasts. However, it is very challenging [...] Read more.

A cloud image can provide significant information, such as precipitation and solar irradiation. Predicting short-time cloud motion from images is the primary means of making intra-hour irradiation forecasts for solar-energy production and is also important for precipitation forecasts. However, it is very challenging to predict cloud motion (especially nonlinear motion) accurately. Traditional methods of cloud-motion prediction are based on block matching and the linear extrapolation of cloud features; they largely ignore nonstationary processes, such as inversion and deformation, and the boundary conditions of the prediction region. In this paper, the prediction of cloud motion is regarded as a spatiotemporal sequence-forecasting problem, for which an end-to-end deep-learning model is established; both the input and output are spatiotemporal sequences. The model is based on gated recurrent unit (GRU)- recurrent convolutional network (RCN), a variant of the gated recurrent unit (GRU), which has convolutional structures to deal with spatiotemporal features. We further introduce surrounding context into the prediction task. We apply our proposed Multi-GRU-RCN model to FengYun-2G satellite infrared data and compare the results to those of the state-of-the-art method of cloud-motion prediction, the variational optical flow (VOF) method, and two well-known deep-learning models, namely, the convolutional long short-term memory (ConvLSTM) and GRU. The Multi-GRU-RCN model predicts intra-hour cloud motion better than the other methods, with the largest peak signal-to-noise ratio and structural similarity index. The results prove the applicability of the GRU-RCN method for solving the spatiotemporal data prediction problem and indicate the advantages of our model for further applications. Full article

(This article belongs to the Special Issue Artificial Intelligence and Machine Learning: Application in Predictive Hydrological Models)

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20 pages, 6624 KiB

Open AccessEditor’s ChoiceArticle

Estimating Surface Downward Longwave Radiation Using Machine Learning Methods

by Chunjie Feng, Xiaotong Zhang, Yu Wei, Weiyu Zhang, Ning Hou, Jiawen Xu, Kun Jia, Yunjun Yao, Xianhong Xie, Bo Jiang, Jie Cheng and Xiang Zhao

Atmosphere 2020, 11(11), 1147; https://doi.org/10.3390/atmos11111147 - 22 Oct 2020

Cited by 15 | Viewed by 2985

Abstract

The downward longwave radiation (L_d, 4–100 μm) is a major component of research for the surface radiation energy budget and balance. In this study, we applied five machine learning methods, namely artificial neural network (ANN), support vector regression (SVR), gradient [...] Read more.

The downward longwave radiation (L_d, 4–100 μm) is a major component of research for the surface radiation energy budget and balance. In this study, we applied five machine learning methods, namely artificial neural network (ANN), support vector regression (SVR), gradient boosting regression tree (GBRT), random forest (RF), and multivariate adaptive regression spline (MARS), to estimate L_d using ground measurements collected from 27 Baseline Surface Radiation Network (BSRN) stations. L_d measurements in situ were used to validate the accuracy of L_d estimation models on daily and monthly time scales. A comparison of the results demonstrated that the estimates on the basis of the GBRT method had the highest accuracy, with an overall root-mean-square error (RMSE) of 17.50 W m⁻² and an R value of 0.96 for the test dataset on a daily time scale. These values were 11.19 W m⁻² and 0.98, respectively, on a monthly time scale. The effects of land cover and elevation were further studied to comprehensively evaluate the performance of each machine learning method. All machine learning methods achieved better results over the grass land cover type but relatively worse results over the tundra. GBRT, RF, and MARS methods were found to show good performance at both the high- and low-altitude sites. Full article

(This article belongs to the Special Issue Machine Learning for Solar Radiation Estimation)

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26 pages, 3753 KiB

Open AccessEditor’s ChoiceReview

Thermal Environment of Urban Schoolyards: Current and Future Design with Respect to Children’s Thermal Comfort

by Dimitrios Antoniadis, Nikolaos Katsoulas and Dimitris Κ. Papanastasiou

Atmosphere 2020, 11(11), 1144; https://doi.org/10.3390/atmos11111144 - 22 Oct 2020

Cited by 36 | Viewed by 6440

Abstract

Urban outdoor thermal conditions, and its impacts on the health and well-being for the city inhabitants have reached increased attention among biometeorological studies during the last two decades. Children are considered more sensitive and vulnerable to hot ambient conditions compared to adults, and [...] Read more.

Urban outdoor thermal conditions, and its impacts on the health and well-being for the city inhabitants have reached increased attention among biometeorological studies during the last two decades. Children are considered more sensitive and vulnerable to hot ambient conditions compared to adults, and are affected strongly by their thermal environment. One of the urban outdoor environments that children spend almost one third of their school time is the schoolyard. The aims of the present manuscript were to review studies conducted worldwide, in order to present the biophysical characteristics of the typical design of the urban schoolyard. This was done to assess, in terms of bioclimatology, the interactions between the thermal environment and the children’s body, to discuss the adverse effects of thermal environment on children, especially the case of heat stress, and to propose measures that could be applied to improve the thermal environment of schoolyards, focusing on vegetation. Human thermal comfort monitoring tools are mainly developed for adults, thus, further research is needed to adapt them to children. The schemes that are usually followed to design urban schoolyards create conditions that favour the exposure of children to excessive heat, inducing high health risks to them. The literature survey showed that typical urban schoolyard design (i.e., dense surface materials, absence of trees) triggered high surface temperatures (that may exceed 58 °C) and increased absorption of radiative heat load (that may exceed 64 °C in terms of Mean Radiant Temperature) during a clear day with intense solar radiation. Furthermore, vegetation cover has a positive impact on schoolyard’s microclimate, by improving thermal comfort and reducing heat stress perception of children. Design options for urban schoolyards and strategies that can mitigate the adverse effects of heat stress are proposed with focus on vegetation cover that affect positively their thermal environment and improve their aesthetic and functionality. Full article

(This article belongs to the Special Issue Challenges in Applied Human Biometeorology)

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35 pages, 15489 KiB

Open AccessEditor’s ChoiceArticle

Satellite-Based Study and Numerical Forecasting of Two Tornado Outbreaks in the Ural Region in June 2017

by Alexander Chernokulsky, Andrey Shikhov, Alexey Bykov and Igor Azhigov

Atmosphere 2020, 11(11), 1146; https://doi.org/10.3390/atmos11111146 - 22 Oct 2020

Cited by 20 | Viewed by 3717

Abstract

Strong tornadoes are common for the European part of Russia but happen rather rare east of the Urals. June 2017 became an exceptional month when two tornado outbreaks occurred in the Ural region of Russia, yielded $3 million damage, and resulted in 1 [...] Read more.

Strong tornadoes are common for the European part of Russia but happen rather rare east of the Urals. June 2017 became an exceptional month when two tornado outbreaks occurred in the Ural region of Russia, yielded $3 million damage, and resulted in 1 fatality and 14 injuries. In this study, we performed detailed analysis of these outbreaks with different data. Tornadoes and tornado-related environments were diagnosed with news and eyewitness reports, ground-based meteorological observations, sounding data, global numerical weather prediction (NWP) models data, synoptic charts, satellite images, and data of specially conducted aerial imaging. We also estimated the accuracy of short-term forecasting of outbreaks with the WRF-ARW mesoscale atmospheric model, which was run in convection-permitting mode. We determined the formation of 28 tornadoes during the first outbreak (3 June 2017) and 9 tornadoes during the second outbreak (18 June 2017). We estimated their intensity using three different approaches and confirmed that, based on the International Fujita scale (IF), one of the tornadoes had the IF4 intensity, being the first IF4 tornado in Russia in the 21st century and the first-ever IF4 tornado reported beyond the Ural Mountains. The synoptic-scale analysis revealed the similarity of two outbreaks, which both formed near the polar front in the warm part of deepening southern cyclones. Such synoptic conditions yield mostly weak tornadoes in European Russia; however, our analysis indicates that these conditions are likely favorable for strong tornadoes over the Ural region. Meso-scale analysis indicates that the environments were favorable for tornado formation in both cases, and most severe-weather indicators exceeded their critical values. Our analysis demonstrates that for the Ural region, like for other regions of the world, combined use of the global NWP model outputs indicating high values of severe-weather indices and the WRF model forecast outputs explicitly simulating tornadic storm formation could be used to predict the high probability of strong tornado formation. For both analyzed events, the availability of such tornado warning forecast could help local authorities to take early actions on population protection. Full article

(This article belongs to the Special Issue Tornadoes in Europe: Climatology, Forecasting, and Impact)

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12 pages, 1246 KiB

Open AccessEditor’s ChoiceArticle

The Effect of the Covid-19 Lockdown on Air Quality in Three Italian Medium-Sized Cities

by Gabriele Donzelli, Lorenzo Cioni, Mariagrazia Cancellieri, Agustin Llopis Morales and Maria M. Morales Suárez-Varela

Atmosphere 2020, 11(10), 1118; https://doi.org/10.3390/atmos11101118 - 19 Oct 2020

Cited by 69 | Viewed by 6230

Abstract

Despite the societal and economic impacts of the COVID-19 pandemic, the lockdown measures put in place by the Italian government provided an unprecedented opportunity to increase our knowledge of the effect transportation and industry-related emissions have on the air quality in our cities. [...] Read more.

Despite the societal and economic impacts of the COVID-19 pandemic, the lockdown measures put in place by the Italian government provided an unprecedented opportunity to increase our knowledge of the effect transportation and industry-related emissions have on the air quality in our cities. This study assessed the effect of reduced emissions during the lockdown period, due to COVID-19, on air quality in three Italian cities, Florence, Pisa, and Lucca. For this study, we compared the concentration of particulate matter PM₁₀, PM_2.5, NO₂, and O₃ measured during the lockdown period, with values obtained in the same period of 2019. Our results show no evidence of a direct relationship between the lockdown measures implemented and PM reduction in urban centers, except in areas with heavy traffic. Consistent with recently published studies, we did, however, observe a significant decrease in NO₂ concentrations among all the air-monitoring stations for each city in this study. Finally, O₃ levels remained unchanged during the lockdown period. Of note, there were slight variations in the meteorological conditions for the same periods of different years. Our results suggest a need for further studies on the impact of vehicular traffic and industrial activities on PM air pollution, including adopting holistic source-control measures for improved air quality in urban environments. Full article

(This article belongs to the Section Air Quality)

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24 pages, 2868 KiB

Open AccessEditor’s ChoiceArticle

Multifractal Cross Correlation Analysis of Agro-Meteorological Datasets (Including Reference Evapotranspiration) of California, United States

by Adarsh Sankaran, Jaromir Krzyszczak, Piotr Baranowski, Archana Devarajan Sindhu, Nandhineekrishna Pradeep Kumar, Nityanjali Lija Jayaprakash, Vandana Thankamani and Mumtaz Ali

Atmosphere 2020, 11(10), 1116; https://doi.org/10.3390/atmos11101116 - 18 Oct 2020

Cited by 13 | Viewed by 3407

Abstract

The multifractal properties of six acknowledged agro-meteorological parameters, such as reference evapotranspiration (ET0), wind speed (U), incoming solar radiation (SR), air temperature (T), air pressure (P), and relative air humidity (RH) of five stations in California, USA were examined. The investigation of multifractality [...] Read more.

The multifractal properties of six acknowledged agro-meteorological parameters, such as reference evapotranspiration (ET0), wind speed (U), incoming solar radiation (SR), air temperature (T), air pressure (P), and relative air humidity (RH) of five stations in California, USA were examined. The investigation of multifractality of datasets from stations with differing terrain conditions using the Multifractal Detrended Fluctuation Analysis (MFDFA) showed the existence of a long-term persistence and multifractality irrespective of the location. The scaling exponents of SR and T time series are found to be higher for stations with higher altitudes. Subsequently, this study proposed using the novel multifractal cross correlation (MFCCA) method to examine the multiscale-multifractal correlations properties between ET0 and other investigated variables. The MFCCA could successfully capture the scale dependent association of different variables and the dynamics in the nature of their associations from weekly to inter-annual time scales. The multifractal exponents of P and U are consistently lower than the exponents of ET0, irrespective of station location. This study found that joint scaling exponent was nearly the average of scaling exponents of individual series in different pairs of variables. Additionally, the α-values of joint multifractal spectrum were lower than the α values of both of the individual spectra, validating two universal properties in the MFCCA studies for agro-meteorological time series. The temporal evolution of cross-correlation determined by the MFCCA successfully captured the dynamics in the nature of associations in the P-ET0 link. Full article

(This article belongs to the Special Issue Climate Change and Agrometeorological Time Series)

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15 pages, 4506 KiB

Open AccessEditor’s ChoiceArticle

SST Warming in Recent Decades in the Gulf Stream Extension Region and Its Impact on Atmospheric Rivers

by Yifei Wu, Yinglai Jia, Rui Ji and Jie Zhang

Atmosphere 2020, 11(10), 1109; https://doi.org/10.3390/atmos11101109 - 16 Oct 2020

Cited by 5 | Viewed by 3147

Abstract

The sea surface temperature (SST) front in the Gulf Stream (GS) extension region is important to synoptic variations in atmosphere. In winter, large amounts of heat and moisture are released from the SST front, modulating the baroclinicity and humidity of the atmosphere, which [...] Read more.

The sea surface temperature (SST) front in the Gulf Stream (GS) extension region is important to synoptic variations in atmosphere. In winter, large amounts of heat and moisture are released from the SST front, modulating the baroclinicity and humidity of the atmosphere, which is important for extratropical cyclones and atmospheric rivers (ARs). In this study, the variation of SST in the North Atlantic in winters since 1981 is investigated using satellite and reanalysis datasets, and a 23-year (1997 to 2019) warming trend of SST in the GS extension region is detected. The increase of SST is mainly distributed along the SST front, with more than 2 °C warming and a northward shift of the SST gradient from 1997 to 2019. Connected with the SST warming, significant increases in turbulent heat flux and moisture release into the atmosphere were found along the ocean front. As a result, baroclinic instability, upward water vapor flux and AR occurrence frequency increased in recent decades. Meanwhile, there was an increase in extreme rainfall along with the increase in AR landfalling on continental Western Europe (especially in the Iberian Peninsula and on the northern coast of the Mediterranean Sea). Full article

(This article belongs to the Section Meteorology)

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11 pages, 266 KiB

Open AccessEditor’s ChoiceArticle

Premature Adult Mortality and Years of Life Lost Attributed to Long-Term Exposure to Ambient Particulate Matter Pollution and Potential for Mitigating Adverse Health Effects in Tuzla and Lukavac, Bosnia and Herzegovina

by Vlatka Matkovic, Maida Mulić, Selma Azabagić and Marija Jevtić

Atmosphere 2020, 11(10), 1107; https://doi.org/10.3390/atmos11101107 - 16 Oct 2020

Cited by 10 | Viewed by 3974

Abstract

Ambient air pollution is one of eight global risk factors for deaths and accounts for 38.44 all causes death rates attributable to ambient PM pollution, while in Bosnia and Herzegovina, it is 58.37. We have estimated health endpoints and possible gains if two [...] Read more.

Ambient air pollution is one of eight global risk factors for deaths and accounts for 38.44 all causes death rates attributable to ambient PM pollution, while in Bosnia and Herzegovina, it is 58.37. We have estimated health endpoints and possible gains if two policy scenarios were implemented and air pollution reduction achieved. Real-world health and recorded PM pollution data for 2018 were used for assessing the health impacts and possible gains. Calculations were performed with WHO AirQ+ software against two scenarios with cut-off levels at country-legal values and WHO air quality recommendations. Ambient PM_2.5 pollution is responsible for 16.20% and 22.77% of all-cause mortality among adults in Tuzla and Lukavac, respectively. Our data show that life expectancy could increase by 2.1 and 2.4 years for those cities. In the pollution hotspots, in reality, there is a wide gap in what is observed and the implementation of the legally binding air quality limit values and, thus, adverse health effects. Considerable health gains and life expectancy are possible if legal or health scenarios in polluted cities were achieved. This estimate might be useful in providing additional health burden evidence as a key component for a clean air policy and action plans. Full article

(This article belongs to the Special Issue Contributions of Aerosol Sources to Health Impacts)

40 pages, 5318 KiB

Open AccessEditor’s ChoiceReview

Air Pollution-Related Brain Metal Dyshomeostasis as a Potential Risk Factor for Neurodevelopmental Disorders and Neurodegenerative Diseases

by Deborah A. Cory-Slechta, Marissa Sobolewski and Günter Oberdörster

Atmosphere 2020, 11(10), 1098; https://doi.org/10.3390/atmos11101098 - 14 Oct 2020

Cited by 14 | Viewed by 5421

Abstract

Increasing evidence links air pollution (AP) exposure to effects on the central nervous system structure and function. Particulate matter AP, especially the ultrafine (nanoparticle) components, can carry numerous metal and trace element contaminants that can reach the brain in utero and after birth. [...] Read more.

Increasing evidence links air pollution (AP) exposure to effects on the central nervous system structure and function. Particulate matter AP, especially the ultrafine (nanoparticle) components, can carry numerous metal and trace element contaminants that can reach the brain in utero and after birth. Excess brain exposure to either essential or non-essential elements can result in brain dyshomeostasis, which has been implicated in both neurodevelopmental disorders (NDDs; autism spectrum disorder, schizophrenia, and attention deficit hyperactivity disorder) and neurodegenerative diseases (NDGDs; Alzheimer’s disease, Parkinson’s disease, multiple sclerosis, and amyotrophic lateral sclerosis). This review summarizes the current understanding of the extent to which the inhalational or intranasal instillation of metals reproduces in vivo the shared features of NDDs and NDGDs, including enlarged lateral ventricles, alterations in myelination, glutamatergic dysfunction, neuronal cell death, inflammation, microglial activation, oxidative stress, mitochondrial dysfunction, altered social behaviors, cognitive dysfunction, and impulsivity. Although evidence is limited to date, neuronal cell death, oxidative stress, and mitochondrial dysfunction are reproduced by numerous metals. Understanding the specific contribution of metals/trace elements to this neurotoxicity can guide the development of more realistic animal exposure models of human AP exposure and consequently lead to a more meaningful approach to mechanistic studies, potential intervention strategies, and regulatory requirements. Full article

(This article belongs to the Special Issue Metals in Ambient Particles: Sources and Effects on Human Health)

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19 pages, 9412 KiB

Open AccessEditor’s ChoiceArticle

A Study of the Thermal Environment and Air Quality in Hot–Humid Regions during Running Events in Southern Taiwan

by Si-Yu Yu, Andreas Matzarakis and Tzu-Ping Lin

Atmosphere 2020, 11(10), 1101; https://doi.org/10.3390/atmos11101101 - 14 Oct 2020

Cited by 6 | Viewed by 2868

Abstract

It is quite difficult to investigate thermal comfort in hot–humid regions, and there have not been many real case studies or research related to this issue. In this article, four running events held in nearby popular travel spots in Kaohsiung, the largest city [...] Read more.

It is quite difficult to investigate thermal comfort in hot–humid regions, and there have not been many real case studies or research related to this issue. In this article, four running events held in nearby popular travel spots in Kaohsiung, the largest city in southern Taiwan, were selected to analyze the influence of thermal environment and air quality on thermal comfort. Mostly real time environmental monitoring data were applied for estimating thermal indicators, along with Sky View Factor (SVF) data taken at the sites of the running scheduled routes, to analyze the thermal performance of participants at running events. Compared with runners, walkers (local residents, fans, and staff of the events) would be exposed to a greater risk of thermal discomfort with increasing time spent on the routes. With the integrated analysis, mPET (modified physiologically equivalent temperature) can be viewed as a relatively comprehensive indicator in considering both environmental thermal conditions and the biometrical differences of activities and clothing types. From the results, a good correlation between mPET and solar radiation/SVF was obtained, which indicated that mPET could be sufficiently sensible in revealing the thermal condition variation from one site to another during the route with time. Based on the discomfort risk assessment, for runners, the event held in autumn with lower SVF at the route sites would be less risky of thermal discomfort, while the event held in spring with lower solar radiation would be more comfortable for walkers. As for air quality condition, the inappropriateness of holding winter outdoor activities in Kaohsiung was obviously shown in both real time monitoring data and long term analysis. Full article

(This article belongs to the Special Issue Challenges in Applied Human Biometeorology)

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19 pages, 7365 KiB

Open AccessEditor’s ChoiceArticle

First Spaceborne Version of Velocity-Azimuth Display Technique for Wind Field Retrieval on Cloud and Precipitation Radar

by Yuexia Wang, Ming Wei and Quan Shi

Atmosphere 2020, 11(10), 1089; https://doi.org/10.3390/atmos11101089 - 13 Oct 2020

Cited by 2 | Viewed by 2434

Abstract

Cloud and precipitation radar mounted on a polar orbiting satellite opens up a new opportunity for global wind observation to improve numerical weather forecasting and prevent weather disasters. However, no related works have been done to retrieve the wind field for spaceborne cloud [...] Read more.

Cloud and precipitation radar mounted on a polar orbiting satellite opens up a new opportunity for global wind observation to improve numerical weather forecasting and prevent weather disasters. However, no related works have been done to retrieve the wind field for spaceborne cloud and precipitation radar. This is mainly because the high-speed motion of satellites makes wind field retrieval complex. This paper developed the first spaceborne version of the velocity–azimuth display (VAD) technique for wind field retrieval, which was originally created for ground-based radar. After derivation of VAD for spaceborne radar, we found that the product of the azimuth of the radar beam and its first harmonic was introduced into the Fourier series of radar radial velocity due to the motion of the satellites. The wind retrieval equations were developed by considering the effects of satellite motion and conical scanning strategy of radar. Numerical simulations of the spaceborne radar showed that the proposed VAD method provided a mean vertical profile of the horizontal wind with high vertical resolution over a large observation swath. Validations on airborne radar data with the same conical scan strategy as the spaceborne radar were carried out to capture the average wind structure in one hurricane event. The real data results demonstrated that the wind-retrieved results by the proposed method were consistent with the ground truth data, indicating the potential use of our proposal for spaceborne radar. Full article

(This article belongs to the Special Issue Developing Algorithms and Software Tools to Retrieve Atmospheric Composition)

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20 pages, 8072 KiB

Open AccessEditor’s ChoiceArticle

A Review and Evaluation of Planetary Boundary Layer Parameterizations in Hurricane Weather Research and Forecasting Model Using Idealized Simulations and Observations

by Jun A. Zhang, Evan A. Kalina, Mrinal K. Biswas, Robert F. Rogers, Ping Zhu and Frank D. Marks

Atmosphere 2020, 11(10), 1091; https://doi.org/10.3390/atmos11101091 - 13 Oct 2020

Cited by 32 | Viewed by 3798

Abstract

This paper reviews the evolution of planetary boundary layer (PBL) parameterization schemes that have been used in the operational version of the Hurricane Weather Research and Forecasting (HWRF) model since 2011. Idealized simulations are then used to evaluate the effects of different PBL [...] Read more.

This paper reviews the evolution of planetary boundary layer (PBL) parameterization schemes that have been used in the operational version of the Hurricane Weather Research and Forecasting (HWRF) model since 2011. Idealized simulations are then used to evaluate the effects of different PBL schemes on hurricane structure and intensity. The original Global Forecast System (GFS) PBL scheme in the 2011 version of HWRF produces the weakest storm, while a modified GFS scheme using a wind-speed dependent parameterization of vertical eddy diffusivity (K_m) produces the strongest storm. The subsequent version of the hybrid eddy diffusivity and mass flux scheme (EDMF) used in HWRF also produces a strong storm, similar to the version using the wind-speed dependent K_m. Both the intensity change rate and maximum intensity of the simulated storms vary with different PBL schemes, mainly due to differences in the parameterization of K_m. The smaller the K_m in the PBL scheme, the faster a storm tends to intensify. Differences in hurricane PBL height, convergence, inflow angle, warm-core structure, distribution of deep convection, and agradient force in these simulations are also examined. Compared to dropsonde and Doppler radar composites, improvements in the kinematic structure are found in simulations using the wind-speed dependent K_m and modified EDMF schemes relative to those with earlier versions of the PBL schemes in HWRF. However, the upper boundary layer in all simulations is much cooler and drier than that in dropsonde observations. This model deficiency needs to be considered and corrected in future model physics upgrades. Full article

(This article belongs to the Special Issue Modeling and Data Assimilation for Tropical Cyclone Forecasts)

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12 pages, 3051 KiB

Open AccessEditor’s ChoiceArticle

Predictors of the Indoor-to-Outdoor Ratio of Particle Number Concentrations in Israel

by Siyu Zhang, Yuval, David M. Broday and Raanan Raz

Atmosphere 2020, 11(10), 1074; https://doi.org/10.3390/atmos11101074 - 9 Oct 2020

Cited by 3 | Viewed by 2672

Abstract

Exposure to airborne particles is a risk factor of many short- and long-term health effects. Most epidemiological studies include estimates of exposure to ambient particles, however, people living in developed countries spend most of their time indoors. This work presents an analysis of [...] Read more.

Exposure to airborne particles is a risk factor of many short- and long-term health effects. Most epidemiological studies include estimates of exposure to ambient particles, however, people living in developed countries spend most of their time indoors. This work presents an analysis of a field campaign of simultaneous measurements of indoor-to-outdoor particle number concentrations (PNCs) in Israel. Fine and coarse PNCs were continuously measured using Dylos DC1700 devices from October 2016 to October 2017. The median outdoor PNC was always higher than the indoor PNC in all the five sampling locations. Outdoor fine PNCs peak during the night and experience a trough in the afternoon. The median of the fine indoor-to-outdoor PNC ratio (IOR) was 0.83, with an inter quartile range (IQR) of 0.59. The median of the coarse IOR was 0.70, with an IQR of 0.77. Lower IORs were experienced at night than during the day, with a daily peak (IOR > 1) around noon. Information about the IOR in different regions and seasons may help epidemiologists and policy makers understand the true health effects of particulate air pollution, and correct their exposure estimations such that they account for indoor exposure as well. Full article

(This article belongs to the Special Issue Air Pollution and Human Exposures in Israel)

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14 pages, 2080 KiB

Open AccessEditor’s ChoiceArticle

A Preliminary Spatial Analysis of the Association of Asthma and Traffic-Related Air Pollution in the Metropolitan Area of Calgary, Canada

by Stefania Bertazzon, Caitlin Calder-Bellamy, Rizwan Shahid, Isabelle Couloigner and Richard Wong

Atmosphere 2020, 11(10), 1066; https://doi.org/10.3390/atmos11101066 - 8 Oct 2020

Cited by 6 | Viewed by 3731

Abstract

We performed a preliminary spatial analysis to assess the association of asthma emergency visits (AEV) with ambient air pollutants (NO₂, PM_2.5, PM₁₀, Black Carbon, and VOCs) over Calgary, Canada. Descriptive analyses identify spatial patterns across the city. [...] Read more.

We performed a preliminary spatial analysis to assess the association of asthma emergency visits (AEV) with ambient air pollutants (NO₂, PM_2.5, PM₁₀, Black Carbon, and VOCs) over Calgary, Canada. Descriptive analyses identify spatial patterns across the city. The spatial patterns of AEV and air pollutants were analyzed by descriptive and spatial statistics (Moran’s I and Getis G). The association between AEV, air pollutants, and socioeconomic status was assessed by correlation and regression. A spatial gradient was identified, characterized by increasing AEV incidence from west to east; this pattern has become increasingly pronounced over time. The association of asthma and air pollution is consistent with the location of industrial areas and major traffic corridors. AEV exhibited more significant associations with BTEX and PM₁₀, particularly during the summer. Over time, AEV decreased overall, though with varying temporal patterns throughout Calgary. AEV exhibited significant and seasonal associations with ambient air pollutants. Socioeconomic status is a confounding factor in AEV in Calgary, and the AEV disparities across the city are becoming more pronounced over time. Within the current pandemic, this spatial analysis is relevant and timely, bearing potential to identify hotspots linked to ambient air pollution and populations at greater risk. Full article

(This article belongs to the Special Issue Traffic-Related Air Pollution and Its Impacts on Human Health)

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27 pages, 1430 KiB

Open AccessEditor’s ChoiceArticle

Framing Climate Services: Logics, Actors, and Implications for Policies and Projects

by Marine Lugen

Atmosphere 2020, 11(10), 1047; https://doi.org/10.3390/atmos11101047 - 30 Sep 2020

Cited by 8 | Viewed by 2961

Abstract

This paper explores how climate services are framed in the literature and possible implications for climate services’ policies and projects. By critically exploring the frames around climate services, the wider objective is to encourage more reflexive and responsible research in the field, particularly [...] Read more.

This paper explores how climate services are framed in the literature and possible implications for climate services’ policies and projects. By critically exploring the frames around climate services, the wider objective is to encourage more reflexive and responsible research in the field, particularly given the huge challenge that climate change represents. By using a framing analysis based on an extensive literature review, five dominant frames were identified. Climate services are mainly framed (1) as a technological innovation, (2) as a market, (3) as an interface between users and producers, (4) as a risk management tool, and (5) from an ethical angle. The predominant frames influence how we think about climate services, shared assumptions, and the way in which policies and projects are designed. To prevent negative effects of climate services on the ground, such as inequalities, the main recommendations include establishing interdisciplinary and transdisciplinary dialogues between different communities of practice and players, increasing empirical and social science research to improve our understanding of this new field, and finally, re-thinking climate services in terms of adaptation rather than as the mere production of new information products. Full article

(This article belongs to the Special Issue Towards Inclusive and Operational Weather and Climate Services to Strengthen Resilience to Climate Change)

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19 pages, 2420 KiB

Open AccessEditor’s ChoiceArticle

Verification of Weather and Seasonal Forecast Information Concerning the Peri-Urban Farmers’ Needs in the Lower Ganges Delta in Bangladesh

by Spyridon Paparrizos, Wouter Smolenaars, Talardia Gbangou, Erik van Slobbe and Fulco Ludwig

Atmosphere 2020, 11(10), 1041; https://doi.org/10.3390/atmos11101041 - 29 Sep 2020

Cited by 13 | Viewed by 4094

Abstract

Skillful weather and seasonal predictions have considerable socio-economic potential and could provide meaningful information to farmers and decision-makers towards agricultural planning and decision-making. Peri-urban farmers in the Lower Ganges Delta need skillful forecast information to deal with increased hydroclimatic variability. In the current [...] Read more.

Skillful weather and seasonal predictions have considerable socio-economic potential and could provide meaningful information to farmers and decision-makers towards agricultural planning and decision-making. Peri-urban farmers in the Lower Ganges Delta need skillful forecast information to deal with increased hydroclimatic variability. In the current study, verification of European Centre for Medium-Range Weather Forecasts’ System 5 (ECMWF SEAS5) seasonal prediction system is performed against ground observations for the Lower Ganges Delta using three skills assessment metrics. Additionally, meteoblue hindcasts are verified for Khulna station according to the peri-urban farmers’ needs and an assessment of onset/offset dates of rainy season is also conducted using the same ground observations. The results indicated that the skill of both examined products is limited during the pre-monsoon and monsoon periods, especially in the west side of the Bay of Bengal. However, during the dry winter season, skill is high, which could lead to potential agricultural benefits concerning irrigation planning. Interannual variability and trend indicated that onset dates have become later and that the length of the rainy season reduced. This could increase the pressure on the already challenging situation the farmers are experiencing, in relation to hydro-climatic variability. Full article

(This article belongs to the Special Issue Agricultural Production in Relation to Local and Regional Climate Change)

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24 pages, 4139 KiB

Open AccessEditor’s ChoiceArticle

Intercomparison Study of the Impact of Climate Change on Renewable Energy Indicators on the Mediterranean Islands

by Alba de la Vara, Claudia Gutiérrez, Juan Jesús González-Alemán and Miguel Ángel Gaertner

Atmosphere 2020, 11(10), 1036; https://doi.org/10.3390/atmos11101036 - 27 Sep 2020

Cited by 15 | Viewed by 3309

Abstract

The enhanced vulnerability of insular regions to climate change has been recently recognized by the European Union, which highlights the importance of undertaking adaptation and mitigation strategies according to the specific singularities of the islands. In general, islands are highly dependent on energy [...] Read more.

The enhanced vulnerability of insular regions to climate change has been recently recognized by the European Union, which highlights the importance of undertaking adaptation and mitigation strategies according to the specific singularities of the islands. In general, islands are highly dependent on energy imports which, in turn, feature a marked seasonal demand. Efforts to reduce greenhouse gas emissions in these regions can therefore fulfill a twofold objective: (i) to increase the renewable energy share for global decarbonization and (ii) to reduce the external energy dependence for isolated (or interconnected) systems in which this can only be achieved with an increase of the renewable energy share. However, the increase in renewable technologies makes energy generation more dependent on future climate and its variability. The main aim of this study is to analyze future projections of wind and photovoltaic potential, as well as energy productivity droughts, on the main Euro-Mediterranean islands. Due to the limitations in land surface available in the islands for the installation of renewable energy capacity, the analysis is extended to offshore wind and photovoltaic energy, which may have an important role in the future increases of renewable energy share. To that end, we use climate variables from a series of simulations derived from Euro-CORDEX (Coordinated Downscaling Experiment) simulations for the RCP2.6 and RCP8.5 emission scenarios. A special effort is performed to normalize projected changes and the associated uncertainties. The obtained normalized changes make it easier the intercomparison between the results obtained in the different islands and constitute condensed and valuable information that aims to facilitate climate-related policy decision making for decarbonization and Blue Growth in the islands. Full article

(This article belongs to the Special Issue Climate Change and Blue Economy in Islands)

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17 pages, 1175 KiB

Open AccessEditor’s ChoiceArticle

Observational Practices for Urban Microclimates Using Meteorologically Instrumented Unmanned Aircraft Systems

by Kevin Adkins, Peter Wambolt, Adrian Sescu, Christopher Swinford and Nickolas D. Macchiarella

Atmosphere 2020, 11(9), 1008; https://doi.org/10.3390/atmos11091008 - 21 Sep 2020

Cited by 8 | Viewed by 3313

Abstract

The urban boundary layer (UBL) is one of the most important and least understood atmospheric domains and, consequently, warrants deep understanding and rigorous analysis via sophisticated experimental and numerical tools. When field experiments have been undertaken, they have primarily been accomplished with either [...] Read more.

The urban boundary layer (UBL) is one of the most important and least understood atmospheric domains and, consequently, warrants deep understanding and rigorous analysis via sophisticated experimental and numerical tools. When field experiments have been undertaken, they have primarily been accomplished with either a coarse network of in-situ sensors or slow response sensors based on timing or Doppler shifts, resulting in low resolution and decreasing performance with height. Small unmanned aircraft systems (UASs) offer an opportunity to improve on traditional UBL observational strategies that may require substantive infrastructure or prove impractical in a vibrant city, prohibitively expensive, or coarse in resolution. Multirotor UASs are compact, have the ability to take-off and land vertically, hover for long periods of time, and maneuver easily in all three spatial dimensions, making them advantageous for probing an obstacle-laden environment. Fixed-wing UASs offer an opportunity to cover vast horizontal and vertical distances, at low altitudes, in a continuous manner with high spatial resolution. Hence, fixed-wing UASs are advantageous for observing the roughness sublayer above the highest building height where traditional manned aircraft cannot safely fly. This work presents a methodology for UBL investigations using meteorologically instrumented UASs and discusses lessons learned and best practices garnered from a proof of concept field campaign that focused on the urban canopy layer and roughness sublayer of a large modern city with a high-rise urban canopy. Full article

(This article belongs to the Special Issue Interaction between Urban Microclimates and the Buildings)

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14 pages, 4195 KiB

Open AccessEditor’s ChoiceArticle

The GPM Validation Network and Evaluation of Satellite-Based Retrievals of the Rain Drop Size Distribution

by Patrick N. Gatlin, Walter A. Petersen, Jason L. Pippitt, Todd A. Berendes, David B. Wolff and Ali Tokay

Atmosphere 2020, 11(9), 1010; https://doi.org/10.3390/atmos11091010 - 21 Sep 2020

Cited by 29 | Viewed by 4444

Abstract

A unique capability of the Global Precipitation Measurement (GPM) mission is its ability to better estimate the raindrop size distribution (DSD) on a global scale. To validate the GPM DSD retrievals, a network of more than 100 ground-based polarimetric radars from across the [...] Read more.

A unique capability of the Global Precipitation Measurement (GPM) mission is its ability to better estimate the raindrop size distribution (DSD) on a global scale. To validate the GPM DSD retrievals, a network of more than 100 ground-based polarimetric radars from across the globe are utilized within the broader context of the GPM Validation Network (VN) processing architecture. The GPM VN ensures quality controlled dual-polarimetric radar moments for use in providing reference estimates of the DSD. The VN DSD estimates are carefully geometrically matched with the GPM core satellite measurements for evaluation of the GPM algorithms. We use the GPM VN to compare the DSD retrievals from the GPM’s Dual-frequency Precipitation Radar (DPR) and combined DPR–GPM Microwave Imager (GMI) Level-2 algorithms. Results suggested that the Version 06A GPM core satellite algorithms provide estimates of the mass-weighted mean diameter (D_m) that are biased 0.2 mm too large when considered across all precipitation types. In convective precipitation, the algorithms tend to overestimate D_m by 0.5–0.6 mm, leading the DPR algorithm to underestimate the normalized DSD intercept parameter (N_w) by a factor of two, and introduce a significant bias to the DPR retrievals of rainfall rate for DSDs with large D_m. The GPM Combined algorithm performs better than the DPR algorithm in convection but provides a severely limited range of N_w estimates, highlighting the need to broaden its a priori database in convective precipitation. Full article

(This article belongs to the Special Issue Measurement and Modeling of the Precipitation Particle Size Distribution)

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16 pages, 1058 KiB

Open AccessEditor’s ChoiceArticle

Assessment of Children’s Potential Exposure to Bioburden in Indoor Environments

by Carla Viegas, Beatriz Almeida, Marta Dias, Liliana Aranha Caetano, Elisabete Carolino, Anita Quintal Gomes, Tiago Faria, Vânia Martins and Susana Marta Almeida

Atmosphere 2020, 11(9), 993; https://doi.org/10.3390/atmos11090993 - 17 Sep 2020

Cited by 14 | Viewed by 3396

Abstract

The exposure to particles and bioaerosols has been associated with the increase in health effects in children. The objective of this study was to assess the indoor exposure to bioburden in the indoor microenvironments more frequented by children. Air particulate matter (PM) and [...] Read more.

The exposure to particles and bioaerosols has been associated with the increase in health effects in children. The objective of this study was to assess the indoor exposure to bioburden in the indoor microenvironments more frequented by children. Air particulate matter (PM) and settled dust were sampled in 33 dwellings and four schools with a medium volume sampler and with a passive method using electrostatic dust collectors (EDC), respectively. Settled dust collected by EDC was analyzed by culture-based methods (including azole resistance profile) and using qPCR. Results showed that the PM2.5 and PM10 concentrations in classrooms (31.15 μg/m³ and 57.83 μg/m³, respectively) were higher than in homes (15.26 μg/m³ and 18.95 μg/m³, respectively) and highly exceeded the limit values established by the Portuguese legislation for indoor air quality. The fungal species most commonly found in bedrooms was Penicillium sp. (91.79%), whereas, in living rooms, it was Rhizopus sp. (37.95%). Aspergillus sections with toxigenic potential were found in bedrooms and living rooms and were able to grow on VOR. Although not correlated with PM, EDC provided information regarding the bioburden. Future studies, applying EDC coupled with PM assessment, should be implemented to allow for a long-term integrated sample of organic dust. Full article

(This article belongs to the Special Issue Indoor Air Quality—What Is Known and What Needs to Be Done)

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18 pages, 2930 KiB

Open AccessEditor’s ChoiceArticle

Better Agronomic Management Increases Climate Resilience of Maize to Drought in Tanzania

by Wei Xiong and Elena Tarnavsky

Atmosphere 2020, 11(9), 982; https://doi.org/10.3390/atmos11090982 - 14 Sep 2020

Cited by 7 | Viewed by 3981

Abstract

Improved access to better seeds and other inputs, as well as to market and financing, provides greater harvest security for smallholder farmers in Africa, boosting their incomes and increasing food security. Since 2015, a variety of agronomic measures have been introduced and adopted [...] Read more.

Improved access to better seeds and other inputs, as well as to market and financing, provides greater harvest security for smallholder farmers in Africa, boosting their incomes and increasing food security. Since 2015, a variety of agronomic measures have been introduced and adopted by smallholder farmers under a program led by the United Nations’ World Food Program (WFP) called the Patient Procurement Platform (PPP). Here, we integrate a variety of agronomic measures proposed by the PPP to more than 20,000 smallholder farmers in Tanzania into 18 management strategies. We apply these across the country through grid-based crop model (DSSAT) simulations in order to quantify their benefits and risk to regional food security and smallholder farmers’ livelihoods. The simulation demonstrates current maize yields are far below potential yields in the country. Simulated yields across the nation were slightly higher than the mean of reported values from 1984 to 2014. Periodic droughts delayed farmers’ sowing and reduced maize yield, leading to high risk and low sustainability of maize production in most of the maize areas of the country. Better agronomic management strategies, particularly the combination of long-maturity, drought tolerance cultivars, with high fertilizer input, can potentially increase national maize production by up to five times, promoting Tanzania as a regional breadbasket. Our study provides detailed spatial and temporal information of the yield responses and their spatial variations, facilitating the adoption of various management options for stakeholders. Full article

(This article belongs to the Special Issue Climate Change and Agrometeorological Time Series)

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19 pages, 6649 KiB

Open AccessEditor’s ChoiceArticle

Urban Spatial Patterns and Heat Exposure in the Mediterranean City of Tel Aviv

by Moshe Mandelmilch, Michal Ferenz, Noa Mandelmilch and Oded Potchter

Atmosphere 2020, 11(9), 963; https://doi.org/10.3390/atmos11090963 - 10 Sep 2020

Cited by 18 | Viewed by 4945

Abstract

This study aims to examine the effect of urban spatial patterns on heat exposure in the city of Tel Aviv using multiple methodologies, Local Climate Zones (LCZ), meteorological measurements, and remote sensing. A Local Climate Zone map of Tel Aviv was created using [...] Read more.

This study aims to examine the effect of urban spatial patterns on heat exposure in the city of Tel Aviv using multiple methodologies, Local Climate Zones (LCZ), meteorological measurements, and remote sensing. A Local Climate Zone map of Tel Aviv was created using Geographic Information System (GIS), and satellite images were used to identify the spatial patterns of the urban heat island (UHI). Climatic variables were measured by fixed meteorological stations and by mobile cross-section. Surface and wall temperatures were obtained by satellite images and a hand-held infrared camera. Meteorological measurements at a height of 2 m showed that during midday the city is ~3.6 °C warmer than the surrounding rural area. The cooling effect of parks was evident only during the hot hours of the day (9:00–17:00). Land Surface Temperature in the southern part of the city was hotter by ~7–9 °C compared to the northern part due to lack of urban vegetation. Hot spots were found in compact midrise forms (LCZ 2) that are not ideal from the climatological perspective. Whereas compact low-rise forms (LCZ 3) were less heat vulnerable. The results of this study suggest that climatologists can provide planners and architects with scientific insight into the causes of and solutions for urban climatic heat exposure. Full article

(This article belongs to the Special Issue Challenges in Applied Human Biometeorology)

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17 pages, 4011 KiB

Open AccessEditor’s ChoiceArticle

Modeling Evaporation of Water Droplets as Applied to Survival of Airborne Viruses

by Leonid A. Dombrovsky, Alexander A. Fedorets, Vladimir Yu. Levashov, Alexei P. Kryukov, Edward Bormashenko and Michael Nosonovsky

Atmosphere 2020, 11(9), 965; https://doi.org/10.3390/atmos11090965 - 10 Sep 2020

Cited by 33 | Viewed by 7910

Abstract

Many viruses, such as coronaviruses, tend to spread airborne inside water microdroplets. Evaporation of the microdroplets may result in a reduction of their contagiousness. However, the evaporation of small droplets is a complex process involving mass and heat transfer, diffusion, convection and solar [...] Read more.

Many viruses, such as coronaviruses, tend to spread airborne inside water microdroplets. Evaporation of the microdroplets may result in a reduction of their contagiousness. However, the evaporation of small droplets is a complex process involving mass and heat transfer, diffusion, convection and solar radiation absorption. Virological studies indicate that airborne virus survival is very sensitive to air humidity and temperature. We employ a model of droplet evaporation with the account for the Knudsen layer. This model suggests that evaporation is sensitive to both temperature and the relative humidity (RH) of the ambient air. We also discuss various mechanisms such as the effect of solar irradiation, the dynamic relaxation of moving droplets in ambient air and the gravitational sedimentation of the droplets. The maximum estimate for the spectral radiative flux in the case of cloudless sky showed that the radiation contribution to evaporation of single water droplets is insignificant. We conclude that at small and even at moderately high levels of RH, microdroplets evaporate within dozens of seconds with the convective heat flux from the air being the dominant mechanism in every case. The numerical results obtained in the paper are in good qualitative agreement with both the published laboratory experiments and seasonal nature of many viral infections. Sophisticated experimental techniques may be needed for in situ observation of interaction of viruses with organic particles and living cells within microdroplets. The novel controlled droplet cluster technology is suggested as a promising candidate for such experimental methodology. Full article

(This article belongs to the Special Issue Levitating Droplet Clusters in Aerosol Science)

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25 pages, 4164 KiB

Open AccessEditor’s ChoiceArticle

Vortex Initialization in the NCEP Operational Hurricane Models

by Qingfu Liu, Xuejin Zhang, Mingjing Tong, Zhan Zhang, Bin Liu, Weiguo Wang, Lin Zhu, Banglin Zhang, Xiaolin Xu, Samuel Trahan, Ligia Bernardet, Avichal Mehra and Vijay Tallapragada

Atmosphere 2020, 11(9), 968; https://doi.org/10.3390/atmos11090968 - 10 Sep 2020

Cited by 22 | Viewed by 4537

Abstract

This paper describes the vortex initialization (VI) currently used in NCEP operational hurricane models (HWRF and HMON, and possibly HAFS in the future). The VI corrects the background fields for hurricane models: it consists of vortex relocation, and size and intensity corrections. The [...] Read more.

This paper describes the vortex initialization (VI) currently used in NCEP operational hurricane models (HWRF and HMON, and possibly HAFS in the future). The VI corrects the background fields for hurricane models: it consists of vortex relocation, and size and intensity corrections. The VI creates an improved background field for the data assimilation and thereby produces an improved analysis for the operational hurricane forecast. The background field after VI can be used as an initial field (as in the HMON model, without data assimilation) or a background field for data assimilation (as in HWRF model). Full article

(This article belongs to the Special Issue Modeling and Data Assimilation for Tropical Cyclone Forecasts)

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37 pages, 769 KiB

Open AccessEditor’s ChoiceArticle

Impact of Urbanization on the Predictions of Urban Meteorology and Air Pollutants over Four Major North American Cities

by Shuzhan Ren, Craig A. Stroud, Stephane Belair, Sylvie Leroyer, Rodrigo Munoz-Alpizar, Michael D. Moran, Junhua Zhang, Ayodeji Akingunola and Paul A. Makar

Atmosphere 2020, 11(9), 969; https://doi.org/10.3390/atmos11090969 - 10 Sep 2020

Cited by 13 | Viewed by 3348

Abstract

The sensitivities of meteorological and chemical predictions to urban effects over four major North American cities are investigated using the high-resolution (2.5-km) Environment and Climate Change Canada’s air quality model with the Town Energy Balance (TEB) scheme. Comparisons between the model simulation results [...] Read more.

The sensitivities of meteorological and chemical predictions to urban effects over four major North American cities are investigated using the high-resolution (2.5-km) Environment and Climate Change Canada’s air quality model with the Town Energy Balance (TEB) scheme. Comparisons between the model simulation results with and without the TEB effect show that urbanization has great impacts on surface heat fluxes, vertical diffusivity, air temperature, humidity, atmospheric boundary layer height, land-lake circulation, air pollutants concentrations and Air Quality Health Index. The impacts have strong diurnal variabilities, and are very different in summer and winter. While the diurnal variations of the impacts share some similarities over each city, the magnitudes can be very different. The underlying mechanisms of the impacts are investigated. The TEB impacts on the predictions of meteorological and air pollutants over Toronto are evaluated against ground-based observations. The results show that the TEB scheme leads to a great improvement in biases and root-mean-square deviations in temperature and humidity predictions in downtown, uptown and suburban areas in the early morning and nighttime. The scheme also leads to a big improvement of predictions of NO

_{x}

, PM

_{2.5}

and ground-level ozone in the downtown, uptown and industrial areas in the early morning and nighttime. Full article

(This article belongs to the Special Issue Extreme Climate Events and Air Quality)

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19 pages, 640 KiB

Open AccessEditor’s ChoiceArticle

Climate and the Global Spread and Impact of Bananas’ Black Leaf Sigatoka Disease

by Eric Strobl and Preeya Mohan

Atmosphere 2020, 11(9), 947; https://doi.org/10.3390/atmos11090947 - 5 Sep 2020

Cited by 8 | Viewed by 5637

Abstract

While Black Sigatoka Leaf Disease (Mycosphaerella fijiensis) has arguably been the most important pathogen affecting the banana industry over the past 50 years, there are no quantitative estimates of what risk factors determine its spread across the globe, nor how its [...] Read more.

While Black Sigatoka Leaf Disease (Mycosphaerella fijiensis) has arguably been the most important pathogen affecting the banana industry over the past 50 years, there are no quantitative estimates of what risk factors determine its spread across the globe, nor how its spread has affected banana producing countries. This study empirically models the disease spread across and its impact within countries using historical spread timelines, biophysical models, local climate data, and country level agricultural data. To model the global spread a empirical hazard model is employed. The results show that the most important factor affecting first time infection of a country is the extent of their agricultural imports, having increased first time disease incidence by 69% points. In contrast, long distance dispersal due to climatic factors only raised this probability by 0.8% points. The impact of disease diffusion within countries once they are infected is modelled using a panel regression estimator. Findings indicate that under the right climate conditions the impact of Black Sigatoka Leaf Disease can be substantial, currently resulting in an average 3% reduction in global annual production, i.e., a loss of yearly revenue of about USD 1.6 billion. Full article

(This article belongs to the Special Issue Plant Adaptation to Global Climate Change)

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12 pages, 2281 KiB

Open AccessEditor’s ChoiceArticle

Dynamics of Mechanical Oscillator Mechanism for Stratospheric Gravity Waves Generated by Convection

by Shiwang Yu, Lifeng Zhang, Ming Zhang and Yuan Wang

Atmosphere 2020, 11(9), 942; https://doi.org/10.3390/atmos11090942 - 3 Sep 2020

Cited by 1 | Viewed by 2292

Abstract

The mechanical oscillator mechanism (MOM) for stratospheric gravity waves generated by convection is investigated with a dynamics model using the two-dimensional, nonhydrostatic and linear governing equations based on the Boussinesq approximation. The model is solved analytically with a fixed buoyancy oscillation (BO) at [...] Read more.

The mechanical oscillator mechanism (MOM) for stratospheric gravity waves generated by convection is investigated with a dynamics model using the two-dimensional, nonhydrostatic and linear governing equations based on the Boussinesq approximation. The model is solved analytically with a fixed buoyancy oscillation (BO) at the tropopause as the boundary conditions. Results show that this BO is the source of stratospheric gravity waves and the MOM is the generation mechanism. The characteristics of the stratospheric gravity waves not only depend on the BO, but also rely on the stratospheric state, such as the background wind and the buoyancy frequency. When the vertical wavenumbers of the stratospheric gravity waves are close to those of the intrinsic characteristic waves (ICWs), which are the model solution without BO forcing at the tropopause, resonance occurs. Under the resonance conditions, the amplitudes of the stratospheric gravity waves increase significantly, even for low BO intensity. The background wind in the stratosphere has a large effect on wave resonance. Finally, numerical simulation results of a low-vortex system also verify that the MOM is the generation mechanism of stratospheric gravity waves generated by convection. Full article

(This article belongs to the Special Issue Gravity Waves in the Atmosphere)

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15 pages, 4270 KiB

Open AccessEditor’s ChoiceArticle

Evaluation of the Antarctic Circumpolar Wave Simulated by CMIP5 and CMIP6 Models

by Zhichao Lu, Tianbao Zhao and Weican Zhou

Atmosphere 2020, 11(9), 931; https://doi.org/10.3390/atmos11090931 - 30 Aug 2020

Cited by 3 | Viewed by 3119

Abstract

As a coupled large-scale oceanic and atmospheric pattern in the Southern Ocean, the Antarctic circumpolar wave (ACW) has substantial impacts on the global climate. In this study, using the European Centre for Medium-Range Weather Forecasts ERA5 dataset and historical experiment outputs from 24 [...] Read more.

As a coupled large-scale oceanic and atmospheric pattern in the Southern Ocean, the Antarctic circumpolar wave (ACW) has substantial impacts on the global climate. In this study, using the European Centre for Medium-Range Weather Forecasts ERA5 dataset and historical experiment outputs from 24 models of the Coupled Model Intercomparison Project Phase 5 and Phase 6 (CMIP5/CMIP6) spanning the 1980s and 1990s, the simulation capability of models for sea-level pressure (SLP) and sea surface temperature (SST) variability of the ACW is evaluated. It is shown that most models can capture well the 50-month period of the ACW. However, many simulations show a weak amplitude, but with various phase differences. Selected models can simulate SLP better than SST, and CMIP6 models generally perform better than the CMIP5 models. The best model for SLP simulation is the CanESM5 model from CMIP6, whereas the best model for SST simulation is the ACCESS1.3 model from CMIP5. It seems that the SST simulation benefits from the inclusion of both a carbon cycle process and a chemistry module, while the SLP simulation benefits from only the chemistry module. When both SLP and SST are taken into consideration, the CanESM5 model performs the best among all the selected models. Full article

(This article belongs to the Section Climatology)

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25 pages, 3885 KiB

Open AccessEditor’s ChoiceArticle

Field Evaluation of Low-Cost PM Sensors (Purple Air PA-II) Under Variable Urban Air Quality Conditions, in Greece

by Iasonas Stavroulas, Georgios Grivas, Panagiotis Michalopoulos, Eleni Liakakou, Aikaterini Bougiatioti, Panayiotis Kalkavouras, Kyriaki Maria Fameli, Nikolaos Hatzianastassiou, Nikolaos Mihalopoulos and Evangelos Gerasopoulos

Atmosphere 2020, 11(9), 926; https://doi.org/10.3390/atmos11090926 - 29 Aug 2020

Cited by 78 | Viewed by 12253

Abstract

Recent advances in particle sensor technologies have led to an increased development and utilization of low-cost, compact, particulate matter (PM) monitors. These devices can be deployed in dense monitoring networks, enabling an improved characterization of the spatiotemporal variability in ambient levels and exposure. [...] Read more.

Recent advances in particle sensor technologies have led to an increased development and utilization of low-cost, compact, particulate matter (PM) monitors. These devices can be deployed in dense monitoring networks, enabling an improved characterization of the spatiotemporal variability in ambient levels and exposure. However, the reliability of their measurements is an important prerequisite, necessitating rigorous performance evaluation and calibration in comparison to reference-grade instrumentation. In this study, field evaluation of Purple Air PA-II devices (low-cost PM sensors) is performed in two urban environments and across three seasons in Greece, in comparison to different types of reference instruments. Measurements were conducted in Athens (the largest city in Greece with nearly four-million inhabitants) for five months spanning over the summer of 2019 and winter/spring of 2020 and in Ioannina, a medium-sized city in northwestern Greece (100,000 inhabitants) during winter/spring 2019–2020. The PM_2.5 sensor output correlates strongly with reference measurements (R² = 0.87 against a beta attenuation monitor and R² = 0.98 against an optical reference-grade monitor). Deviations in the sensor-reference agreement are identified as mainly related to elevated coarse particle concentrations and high ambient relative humidity. Simple and multiple regression models are tested to compensate for these biases, drastically improving the sensor’s response. Large decreases in sensor error are observed after implementation of models, leading to mean absolute percentage errors of 0.18 and 0.12 for the Athens and Ioannina datasets, respectively. Overall, a quality-controlled and robustly evaluated low-cost network can be an integral component for air quality monitoring in a smart city. Case studies are presented along this line, where a network of PA-II devices is used to monitor the air quality deterioration during a peri-urban forest fire event affecting the area of Athens and during extreme wintertime smog events in Ioannina, related to wood burning for residential heating. Full article

(This article belongs to the Section Air Quality)

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